{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\"FMP\"\n", "\"AudioLabs\"\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\"C7\"\n", "

Audio Identification

\n", "
\n", "\n", "
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\n", "Following Section 7.1 of [Müller, FMP, Springer 2015], we discuss in this notebook the task of audio identification. In particular, we present the main ideas of a popular fingerprinting system based on spectral peaks, which was original introduced by Wang (and used in commercial systems such as Shazam).\n", " \n", "

\n", "

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction\n", "\n", "Let us assume you hear a song in a restaurant, in a shopping mall, or in a car, and you want to learn more about it. For example, you want to know the song's title or the name of the performer or the artist. Recent music discovery services help users in such situations by identifying the audio recording and delivering suitable content information. A typical scenario is that a user, also called the **client**, records a short audio fragment of the unknown song using a smartphone. The audio fragment is then converted into so-called **audio fingerprints**, which are compact and descriptive audio features. These fingerprints are transmitted to the identification service, also called the **server**. The server hosts various data resources including a fingerprint database that covers all music recordings to be identified, as well as a metadata database that contains content information linked to these recordings. The server receives the query fingerprints sent by the client and compares them with the fingerprints contained in the database. This step is typically realized by an efficient database look-up supported by suitable index structures. In the case of a successful identification, the server retrieves the content information linked to the identified fingerprints and sends back the desired metadata to the client. The following figure presents a schematic overview of the underlying **client–server model** of the described metadata delivery service. \n", "\n", "\"FMP_C7_F02.png\"\n", "\n", "Within the area of content-based music retrieval, the task of audio identification has received a lot of attention in both academic research and industry. Audio identification techniques have now been integrated into many commercial applications such as broadcast and copyright monitoring, or added-value services for delivering metadata and other content information." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## General Requirements\n", "\n", "Real-world music recognition systems need to be robust and computationally efficient, which leads to a number of technical challenges to be solved. In particular, the audio fingerprints used in such systems need to fulfill certain requirements including high specificity, robustness, compactness, and scalability.\n", "\n", "* **Specificity:** Audio fingerprints should possess a high specificity so that even an audio fragment of only a few seconds suffices to reliably identify the corresponding recording and to distinguish it from millions of others.\n", "* **Robustness:** For a reliable identification, fingerprints need to be robust against background noise and signal distortions such as lossy compression, pitch shifting, time scaling, equalization, or dynamics compression.\n", "* **Compactness:** Audio fingerprints should be small-sized so that they can be transmitted over channels with limited bandwidth and can be easily stored and indexed on the database side.\n", "* **Scalability:** In order to scale to millions of recordings, the computation of audio fingerprints should be simple and efficient—a requirement that is also needed when computing the fingerprints on mobile devices with limited processing power. \n", "\n", "Improving a certain requirement often implies losing performance in some other, and one has to face a delicate trade-off between contradicting principles. For example, boosting the robustness typically leads to an increase of wrong identifications (false positives), thus deteriorating the accuracy of the identification system. Similarly, even though beneficial for computational and compactness reasons, an excessive reduction of the fingerprint size negatively affects the discrimination capability. Conversely, fingerprints of high specificity and robustness may not be usable in practice if their computation requires extensive processing power. We close this section by giving some audio examples (a section of the Beatles song \"Act Naturally\") for signal distortions a fingerprinting system needs to deal with.\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
Short nameType of distortionAudio
OriginalOriginal song\n", " \n", "
TalkingSuperposition with other sources
(e.g., people talking in background)
\n", " \n", "
NoiseSuperposition with Gaussian noise\n", " \n", "
CodingStrong coding artifacts\n", " \n", "
FasterTime scale modification (faster)\n", " \n", "
HigherPitch shifting (higher)\n", " \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Audio Fingerprints Based on Spectral Peaks\n", "\n", "We now describe audio fingerprints that are based on the concept of spectral peaks. Being characteristic points in the time–frequency plane, such peaks often remain unchanged even in the presence of noise and additional sound sources. Peak-based fingerprints, which were introduced by Avery Wang, are now successfully used in commercial audio identification systems.\n", "\n", "Given an audio signal in the form of a sampled waveform, the first step of deriving the fingerprints consists in computing an STFT $\\mathcal{X}$ (see Section 3.1 of [Müller, FMP, Springer 2015]). Recall that $\\mathcal{X}(n,k)$ denotes the $k^{\\mathrm{th}}$ Fourier coefficient for the $n^{\\mathrm{th}}$ time frame, where $k\\in[0:K]$ and $n\\in\\mathbb{Z}$. In the following, an element $k\\in[0:K]$ is also referred to as a **frequency stamp** and an element $n\\in\\mathbb{Z}$ as a **time stamp**. Hence, the coordinates of a Fourier coefficient $\\mathcal{X}(n,k)$ are specified by a time–frequency point $(n,k)\\in\\mathbb{Z}\\times[0:K]$ consisting of a time stamp $n$ and a frequency stamp $k$. In the second step of the fingerprint computation, the STFT representation of the signal is reduced to a sparse set of time–frequency points. To this end, one uses a peak-picking strategy that identifies time–frequency points having a higher magnitude than all their neighbors within a region around the respective points. More precisely, let $\\tau\\in\\mathbb{N}$ and $\\kappa\\in\\mathbb{N}$ be parameters that determine the size of the **neighborhood** in the time and frequency direction, respectively. Then a point $(n_0,k_0)$ is selected as a peak if \n", "\n", "\\begin{equation}\n", " |X(n_0,k_0)| \\geq |X(n,k)|\n", "\\end{equation}\n", "\n", "for all $(n,k) \\in \\big(\\left[n_0-\\tau:n_0+\\tau\\right] \\times \n", "\\left[k_0-\\kappa:k_0+\\kappa\\right]\\big)$.\n", "\n", "These definitions are illustrated by the following figure, which shows a spectrogram and one extracted peak with its local neighborhood. Note that increasing the size of the neighborhood makes it harder for a point to be selected. Thus, the parameters $\\tau$ and $\\kappa$ can be used to adjust the density of the selected peaks and to yield a reasonably uniform coverage\n", "of the time–frequency plane.\n", "\n", "\"FMP_C7_F03a.png\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constellation Map\n", "\n", "The peak selection step reduces a complicated spectrogram representation of the signal to a sparse set of coordinates. Notice that the magnitudes of the peaks are no longer used—only the time and frequency stamps of the peaks are considered, which introduces\n", "a high degree of robustness. In the following, the representation consisting of all peak coordinates is also referred to as a **constellation map**. This name is inspired by the observation that the spectral peak patterns look like groups of stars that form patterns on the celestial sphere. \n", "\n", "\n", "\n", "\n", "\n", "In the following code cell, we provide a naive implementation for extracting a constellation map for given **neighborhood parameters** $\\tau$ and $\\kappa$. In this implementation, we iteratively loop through all time-frequency points and check if the neighborhood condition (specified by $\\kappa$ and $\\tau$) is fulfilled. The figures shows a spectrogram representation along with a constellation map (the extracted peak fingerprints shown in red) for the Beatles example from above. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:47.580879Z", "iopub.status.busy": "2024-02-15T08:39:47.580577Z", "iopub.status.idle": "2024-02-15T08:39:50.942064Z", "shell.execute_reply": "2024-02-15T08:39:50.941454Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import os, sys\n", "import numpy as np\n", "from numba import jit\n", "import librosa\n", "#from scipy import signal\n", "from scipy import ndimage\n", "from matplotlib import pyplot as plt\n", "import IPython.display as ipd\n", "import time\n", "\n", "sys.path.append('..')\n", "import libfmp.b\n", "import libfmp.c2\n", "import libfmp.c6\n", "\n", "%matplotlib inline\n", "\n", "@jit(nopython=True)\n", "def compute_constellation_map_naive(Y, dist_freq=7, dist_time=7, thresh=0.01):\n", " \"\"\"Compute constellation map (naive implementation)\n", "\n", " Notebook: C7/C7S1_AudioIdentification.ipynb\n", "\n", " Args:\n", " Y (np.ndarray): Spectrogram (magnitude)\n", " dist_freq (int): Neighborhood parameter for frequency direction (kappa) (Default value = 7)\n", " dist_time (int): Neighborhood parameter for time direction (tau) (Default value = 7)\n", " thresh (float): Threshold parameter for minimal peak magnitude (Default value = 0.01)\n", "\n", " Returns:\n", " Cmap (np.ndarray): Boolean mask for peak structure (same size as Y)\n", " \"\"\"\n", " # spectrogram dimensions\n", " if Y.ndim > 1:\n", " (K, N) = Y.shape\n", " else:\n", " K = Y.shape[0]\n", " N = 1\n", " Cmap = np.zeros((K, N), dtype=np.bool8)\n", "\n", " # loop over spectrogram\n", " for k in range(K):\n", " f1 = max(k - dist_freq, 0)\n", " f2 = min(k + dist_freq + 1, K)\n", " for n in range(N):\n", " t1 = max(n - dist_time, 0)\n", " t2 = min(n + dist_time + 1, N)\n", " curr_mag = Y[k, n]\n", " curr_rect = Y[f1:f2, t1:t2]\n", " c_max = np.max(curr_rect)\n", " if ((curr_mag == c_max) and (curr_mag > thresh)):\n", " Cmap[k, n] = True\n", " return Cmap\n", "\n", "def plot_constellation_map(Cmap, Y=None, xlim=None, ylim=None, title='',\n", " xlabel='Time (sample)', ylabel='Frequency (bins)',\n", " s=5, color='r', marker='o', figsize=(7, 3), dpi=72):\n", " \"\"\"Plot constellation map\n", "\n", " Notebook: C7/C7S1_AudioIdentification.ipynb\n", "\n", " Args:\n", " Cmap: Constellation map given as boolean mask for peak structure\n", " Y: Spectrogram representation (Default value = None)\n", " xlim: Limits for x-axis (Default value = None)\n", " ylim: Limits for y-axis (Default value = None)\n", " title: Title for plot (Default value = '')\n", " xlabel: Label for x-axis (Default value = 'Time (sample)')\n", " ylabel: Label for y-axis (Default value = 'Frequency (bins)')\n", " s: Size of dots in scatter plot (Default value = 5)\n", " color: Color used for scatter plot (Default value = 'r')\n", " marker: Marker for peaks (Default value = 'o')\n", " figsize: Width, height in inches (Default value = (7, 3))\n", " dpi: Dots per inch (Default value = 72)\n", "\n", " Returns:\n", " fig: The created matplotlib figure\n", " ax: The used axes.\n", " im: The image plot\n", " \"\"\"\n", " if Cmap.ndim > 1:\n", " (K, N) = Cmap.shape\n", " else:\n", " K = Cmap.shape[0]\n", " N = 1\n", " if Y is None:\n", " Y = np.zeros((K, N))\n", " fig, ax = plt.subplots(1, 1, figsize=figsize, dpi=dpi)\n", " im = ax.imshow(Y, origin='lower', aspect='auto', cmap='gray_r', interpolation='nearest')\n", " ax.set_xlabel(xlabel)\n", " ax.set_ylabel(ylabel)\n", " ax.set_title(title)\n", " Fs = 1\n", " if xlim is None:\n", " xlim = [-0.5/Fs, (N-0.5)/Fs]\n", " if ylim is None:\n", " ylim = [-0.5/Fs, (K-0.5)/Fs]\n", " ax.set_xlim(xlim)\n", " ax.set_ylim(ylim)\n", " n, k = np.argwhere(Cmap == 1).T\n", " ax.scatter(k, n, color=color, s=s, marker=marker)\n", " plt.tight_layout()\n", " return fig, ax, im\n", " \n", "def compute_spectrogram(fn_wav, Fs=22050, N=2048, H=1024, bin_max=128, frame_max=None):\n", " x, Fs = librosa.load(fn_wav, Fs)\n", " x_duration = len(x) / Fs\n", " X = librosa.stft(x, n_fft=N, hop_length=H, win_length=N, window='hanning')\n", " if bin_max is None:\n", " bin_max = X.shape[0]\n", " if frame_max is None:\n", " frame_max = X.shape[0]\n", " Y = np.abs(X[:bin_max, :frame_max])\n", " return Y\n", "\n", "wav_dict = {}\n", "wav_dict['Original'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4.wav')]\n", "wav_dict['Noise'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4_NoiseSNR-9.wav')]\n", "wav_dict['Talking'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4_Talking.wav')]\n", "wav_dict['Coding'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4_16kbits.wav')]\n", "wav_dict['Faster'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4_Faster.wav')]\n", "wav_dict['Higher'] = [os.path.join('..', 'data', 'C7', 'FMP_C7_Audio_Beatles_ActNaturally_63-3_73-4_Higher.wav')]\n", "\n", "\n", "fn_wav = wav_dict['Original'][-1]\n", "Y = compute_spectrogram(fn_wav)\n", "\n", "dist_freq = 11 # kappa: neighborhood in frequency direction\n", "dist_time = 3 # tau: neighborhood in time direction\n", "title=r'Constellation map using $\\kappa=%d$, $\\tau=%d$' % (dist_freq, dist_time)\n", "Cmap_naive = compute_constellation_map_naive(Y, dist_freq, dist_time)\n", "fig, ax, im = plot_constellation_map(Cmap_naive, np.log(1 + 1 * Y), \n", " color='r', s=30, title=title)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As an alternative to the naive, iterative implementation, we provide in the next code cell a much faster implementation using the Python package `scipy.ndimage` for multi-dimensional image processing. In the following code cell, we compare the results (which should be the same) and runtimes of the two implementation.\n", "\n", "" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:50.977813Z", "iopub.status.busy": "2024-02-15T08:39:50.977506Z", "iopub.status.idle": "2024-02-15T08:39:51.302166Z", "shell.execute_reply": "2024-02-15T08:39:51.301633Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Runtime of naive (iterative) implementation: 0.00582719 seconds\n", "Runtime of fast (scipy.ndimage) implementation: 0.00055249 seconds\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def compute_constellation_map(Y, dist_freq=7, dist_time=7, thresh=0.01):\n", " \"\"\"Compute constellation map (implementation using image processing)\n", "\n", " Notebook: C7/C7S1_AudioIdentification.ipynb\n", "\n", " Args:\n", " Y (np.ndarray): Spectrogram (magnitude)\n", " dist_freq (int): Neighborhood parameter for frequency direction (kappa) (Default value = 7)\n", " dist_time (int): Neighborhood parameter for time direction (tau) (Default value = 7)\n", " thresh (float): Threshold parameter for minimal peak magnitude (Default value = 0.01)\n", "\n", " Returns:\n", " Cmap (np.ndarray): Boolean mask for peak structure (same size as Y)\n", " \"\"\"\n", " result = ndimage.maximum_filter(Y, size=[2*dist_freq+1, 2*dist_time+1], mode='constant')\n", " Cmap = np.logical_and(Y == result, result > thresh)\n", " return Cmap\n", "\n", "\n", "dist_freq = 7 # kappa: neighborhood in frequency direction\n", "dist_time = 3 # tau: neighborhood in time direction\n", "\n", "start = time.time()\n", "Cmap_naive = compute_constellation_map_naive(Y, dist_freq, dist_time)\n", "end = time.time()\n", "print('Runtime of naive (iterative) implementation: %.8f seconds' % (end - start))\n", "\n", "start = time.time()\n", "for i in range(100):\n", " Cmap = compute_constellation_map(Y, dist_freq, dist_time)\n", "end = time.time()\n", "print('Runtime of fast (scipy.ndimage) implementation: %.8f seconds' % ((end - start)/100))\n", "\n", "fig, ax, im = plot_constellation_map(Cmap_naive, np.log(1 + 1 * Y), color='r', s=30)\n", "n, k = np.argwhere(Cmap == 1).T\n", "ax.scatter(k, n, color='cyan', s=5, marker='o')\n", "plt.legend(['Naive implementation', 'Implementation using scipy.ndimage'], \n", " loc='upper right', framealpha=1);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Robustness of Constellation Maps\n", "\n", "As described before, a fingerprinting system should be robust against background noise and signal distortions. In the following code cell, we show the constellation maps for the original Beatles example (`Original`), for the version superimposed with Gaussian noise (`Noise`), for the version with background noise (`Talking`), as well as for the version distorted by coding artifacts (`Coding`). Furthermore, we illustrate how the density of the constellation map can be controlled by the neighborhood parameters $\\kappa$ and $\\tau$. In both parameter settings, one can observe the following:\n", "\n", "* The constellation maps of the distorted versions share some peaks with the original version. \n", "* The peaks of the distorted versions are sometimes slightly shifted in time and/or frequency compared with the ones of the original version." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:51.305259Z", "iopub.status.busy": "2024-02-15T08:39:51.305040Z", "iopub.status.idle": "2024-02-15T08:39:51.785764Z", "shell.execute_reply": "2024-02-15T08:39:51.785217Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def compare_constellation_maps_Beatles(dist_freq = 11, dist_time = 3, wav_dict=wav_dict):\n", " fn_wav = wav_dict['Original'][-1]\n", " Y = compute_spectrogram(fn_wav)\n", " Cmap = compute_constellation_map(Y, dist_freq, dist_time)\n", "\n", " fn_wav = wav_dict['Noise'][-1]\n", " Y_noise = compute_spectrogram(fn_wav)\n", " Cmap_noise = compute_constellation_map(Y_noise, dist_freq, dist_time)\n", "\n", " fn_wav = wav_dict['Talking'][-1]\n", " Y_noise = compute_spectrogram(fn_wav)\n", " Cmap_talking = compute_constellation_map(Y_noise, dist_freq, dist_time)\n", "\n", " fn_wav = wav_dict['Coding'][-1]\n", " Y_coding = compute_spectrogram(fn_wav)\n", " Cmap_coding = compute_constellation_map(Y_coding, dist_freq, dist_time)\n", "\n", " title=r'Constellation maps using $\\kappa=%d$, $\\tau=%d$' % (dist_freq, dist_time)\n", " fig, ax, im = plot_constellation_map(Cmap, color='r', s=50,title=title)\n", " \n", " n, k = np.argwhere(Cmap_noise == 1).T\n", " ax.scatter(k, n, color='cyan', s=20, marker='o')\n", " \n", " n, k = np.argwhere(Cmap_talking == 1).T\n", " ax.scatter(k, n, color='blue', s=40, marker='+')\n", "\n", " n, k = np.argwhere(Cmap_coding == 1).T\n", " ax.scatter(k, n, color='k', s=30, marker='x')\n", " plt.legend(['Original', 'Noise', 'Talking', 'Coding'], loc='upper right', framealpha=1)\n", " return Cmap, Cmap_noise, Cmap_talking, Cmap_coding\n", " \n", "compare_constellation_maps_Beatles(dist_freq = 11, dist_time = 3)\n", "compare_constellation_maps_Beatles(dist_freq = 17, dist_time = 5);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Evaluation Measures for Peak Matching\n", "\n", "In practice, it turns out that even a small percentage of coinciding peaks (while allowing a small tolerance in time and frequency direction) is often sufficient to successfully identify a recording even in the presence of distortions. This observation is the basis for the matching procedure to be described below. We now introduce some **evaluation measures** that indicate the agreement between two constellation maps. We interpret the first constellation map as **reference** (its peaks being considered **relevant**) and the second one as **estimation** (its peaks being considered **estimated**). This allows us to use terms such as **true positives** (TP), **false positives** (FP), and **false negatives** (FN), which we introduced in the [FMP notebook on evaluation](../C4/C4S5_Evaluation.html) in the context of [music structure analysis](../C4/C4.html). In the following code cell, we implement a function for measuring TP, FP, and FN values, while allowing some **tolerance**. A similar concept was used in the context of [boundary evaluation](../C4/C4S5_Evaluation.html), see also Section 4.5.4 of [Müller, FMP, Springer 2015]. We continue with our Beatles example considering the original, noise, coding, and talking versions." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:51.788425Z", "iopub.status.busy": "2024-02-15T08:39:51.788225Z", "iopub.status.idle": "2024-02-15T08:39:52.626593Z", "shell.execute_reply": "2024-02-15T08:39:52.626018Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "====== Reference: Original; Estimation: Noise ======\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "====== Reference: Original; Estimation: Noise ======\n" ] }, { "data": { "image/png": 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tt9nTtSv7NjXRtaWl/fFBaqte4HFbasEsJdiX2ML41Vdf3a6qxR3+UNWc3caOHat6772qhYWq0HErLFSdP1+9Zpsan5XbPE9ZddJ9k9q2xWcM1DXjxmmfnTvbFbz3rl26Ztw4fWDywLZj02LOnMj3L7TNnZt2eZIiC880JXbvVi0qipzPoiLV2tps59Dg4/ONio/3xpM67wNe5cuTdFJtQwnUFfc7asbdP9KC+nrts3OnFtTX65Ly8rZjG/btojdfMDSwzyslPGxLS1S1QI2XqALndzSAtRpBBub0CBwwPfz6SD5XMPs3e2sYvBTjxaI7ZpHiAlLwKRiDp2c+vfdHy3yq582jqXt7/x7N3bpRVl3N+It+znkzZ6d/0SFDoLAw8n0sLIRDUwzJXVvLlGc+oaSqEVrmQ3k5FCXgGtirZ1pbC8uXm/SGDEn8+omyfHnknjiY/cuXw2wPnk+6+PV8Y+HXvUm1TuUKXpUv1TaUUF0xS7Gb9u3Dw9NvpKlHAY09jVPG2QsXcsqTT1K8fTsFe1pNOfIJj9pSNUaONLI36sxsjKvFjsPsGESS6rmyZXoEvk1NT8mdiQJV3VZba/IxZ4753L3bmws6o5gl5eVaUF+vvXft2tvL9XKE5xotbevXT9eMG6fb+vVLb7T03HOqRUVaWdLfpFdaatJ67rn453rxTJ3rt6VTWJj49RMl3d747t3+1JtI1/F4NBx3FirCvWlXt1IZ9adTp/xm92699odH6w2XTtFtf/pTas/SKV/Dvl3Sr7OptqEk6soaVe2zZ0/E2UG/3r9pz3ym2+Y8aktr1Iy82907Z38kiDICz7oQTmcbO3ZsRqcxI9705mZdM2mSf4IiUy+t557TJTNntp8OmzkzteuEOh7Tp3ecXkvkmaT7TNM4P6mXRDodjUx0MHy6XkJTf2H3pkNdePLJ5C6abp3yEy/ajted6HTaUIJ1ZZuqFrS2th/Q1Nen3/mPQDLTzVHxqg14kE7UwWCU46MJ8JxeRjZu3Dhdu3YtPP88TJ5spubq681URpcusHIlHJdy8J8OVGMiabgnhQoaGqgsLaV4e1js+aIi2LrVG0OmujpuuXQsJVWNnDft52ZazWMDqWqgVJXGvRG4KFClUiShKZ0TFp3Q9n3KM59QvmoXh298v21qDcy9emfoYJad1peVxw8AwlQGbtJ5pvPnw+WXR5/muu22iNO3SatHamuhpMR8hhPr+ad6XrrU1Zmp682bzVRfCvUoYhvA+HltV09cZazu14/Sysr2dSGBuuV5nfKD2lqqR46k9O23O+Sr8sgjKX7zzaj3OLx8lyzdzIqvncvsBQvo3tREU/fuLJg1i7NXPMQd3zw0+fIl0IaamprYsmULDQ0NKRXf4i09e/bkkEMOoXuY2lREXlXVDhEAfdOBi8hCYCqwTVWHO/t+DZyJeT9uAS5Q1V3Ofz/BvD8/By7VZNzlHXeceeml+XKKRzHmpT4bE4GiuaWFBd//fkfhDd7qQHv1amu8nui8I1ABdBdp92LuJkIFSepkgJKqRqoGDKJ7U1O7l1q35maqBgyipKoqxtkO6TzTFPR/KemkiorMyzDaS7JXL6ox97bMnU4S+uGI56dKr15p18cKTAenXT1x9rfLn+veVBxxRMe6kGTd8qROeUS44J1wUP+I+XrnoP7cd+nYhARvSVUjdUX7M3vBAhp79uygU05Jl5xAG9qyZQt9+/blsMMOo0s+WYvnIK2trVRVVbFlyxaOOOKIhM7x04htESbYgDuu9irgJ6raIiI3Az8BrhKRYZigFEdiYvquFpGhutcJf3w8eDklwgzMS70CKPvlLyn+Y4ew4QYfDOj8pAzTq3LTzN64lfHwxfgu1WeagqFJBQkKpnBivCSjjugT7GD4bTCZCmUkUU+ce1P217/S5BJuMc9xkRWDziQpqWrk8I07Iubr8I3v8UHfgqjnhpfvlbo/RuwIVBxxBOdNOz+18sVpQw0NDVZ4B4QuXbpw4IEHsnXr1sRPijSv7tWGaaNvRfnva8Bi5/tPMII99N/jwDHx0h87dmzCOgdfyJXlTgkS0jP11jT0TKqZM76Lc/1k9H/J6qTiETO9BOqN1/nxklTqSdp1K9t1KhrOs4yYr2TeAbt367ayMi2or++oUy4r8618a9euTfqcvFoWFkAiPROyYcQWR4D/DfiW8/3O0Hfn9wLgnCjnXYiJE7t20KBB3t21VMiVdcBJ4Nka92xbDKdgaOJZB0bjWJkmUG+StVJNlnSfcyrnp123sl2nIuGl8ZnLGK6tI5CqIWmCWAEePJIR4FlZBy4iP8U4oVkc2hXhsIjWdar6B+APYIzYfMlgoiSgA801ivFA1wpt06fLLh1LSVUV4y/yx/gu3vWT0aG3U4+Q3n0oI8ZUcwL1Jub5aeLF1Hwq9STtupXtOhUJ17PsVbuD8Wu3m2cZ2p9M3o47jhmjR7PhJyfRVfrx/fEzKL7jjpx8j1gyQ8YFuIicjzFuO9npWQB8hAnWHuKLQBKKgCySIQO6nCQDxnfxrp+sDt2rDkwHg0fnd1vacepN3PNTxDMHEtki23UqEs6zvMOLlSK9evHsmB5AHdee1zmC54kI3/rWt/jTn/4EQEtLCwMGDODoo4/m73//e9Tz1q1bx9atW5k8eXLM9Hv16kVdXZ2neW5sbOT000/n9ttv5/zzzwfggw8+oE+fPvTp04d+/foxf/58jjjiCA477DCampo4/vjjufvuu/n000/59re/zT//+c+085FRAS4ipwNXAZNU1b1u4VFgiYj8H8aIbQiwJpN5S4sMGdBZcou4I/o49cbLGYEQFaRorGeJTRA7FjlCYWEhb731Fo2NjRQUFLBq1SpKSkrinrdu3TrWrl0bV4D7wcKFC5k2bRqjRo1i3bp1AMycOZOpU6dyzjnnAFBRUcEhhxzCunXraGlp4aSTTmLFihVMmzaNAQMG8MILLzBx4sS08uGb6aGILMX43DtMRD4SkdkYXXcRsEpE1onIPQCq+jbwILAe+CfwA03GAt0SWJ6e+XRm1+UGjGJgPKkLx3TPD6cM/6bmM0W+16l8L18kzjjjDP7xj38AsHTpUmbM2KvUWbNmDcceeyxjxozh2GOP5d1336WpqYlrr72W5cuXM3r0aJYvX05dXR0XXHABI0aMYOTIkTz88MNtafz0pz9l1KhRTJgwgSpnyWF1dTVf//rXGT9+POPHj+eFF14A4JlnnmH06NGMHj2aMWPGUBvBX8PixYs566yzEi5f165dOfbYY9nsrDA5++yzWbx4cZyzEkg37RSioKqR1GoLYhx/I3CjX/mxWCz+Tc1bMuxAJgO417u7eabymZj/p3Ifpk+fzg033MDUqVN54403mDVrFs899xwAhx9+OM8++yxdu3Zl9erVXH311Tz88MPccMMNrF27ljvvvBOAq666ij59+vDmm28CsHPnTgDq6+uZMGECN954I3PmzOHee+/lmmuu4bLLLuNHP/oRxx13HB988AFf+cpX2LBhA7feeit33XUXEydOpK6ujh49erTLa1NTE++99x5lZWUJl6+hoYEnn3ySG264AYBx48ZxzTXXJH2fwsn9YCYWiyUp/Jiazzh+B6pJgpAgyzcBnklGjhxJRUUFS5cu7TAlXlNTw/nnn8+mTZsQEZqbmyOmsXr1apYtW9b2e7/99gOge/fuTJ06FYCxY8eyatWqtuPXr1/fdvzu3bupra1l4sSJXHHFFZx33nlMmzaNL37xi+2us337dvr27ZtQubZs2cLo0aMREc466yzOOOMMAPr375/ceu8odCoB7lVD86PBeupxy2KJg2erDbJBJBehV1zhuevkfKc6zv/R3m9+dVi++tWv8uMf/5inn36aTz/9tG3/z372M0488UT+8pe/UFFRwQknnBDxfFVFpOOCpm7durXt32effWhxYpa3trby0ksvUVDQ3tnO3LlzmTJlCitXrmTChAmsXr2aww8/vO3/goICPvvss4TKFNKBh/PZZ591uG4qWPc7AWApxr/0qc7n0uxmx2IJLrW1RnjX1u71Zldfv3e/x9bG+UxFtjMQxqxZs7j22msZMWJEu/01NTVtRm2LFi1q219UVNROP33aaae1TafD3in0aIQfHxK0W7ZsYcSIEVx11VWMGzeOd955p915++23H59//nnCQjwSGzduZPjw4SmfH8IK8CzjXtZT43zOJn7v2GLJFaqBV/CoTifiRz6TOPG7L3zwPRNEJ1KAmoBSlu0MhPHFL36Ryy67rMP+OXPm8JOf/ISJEyfy+ed7bZtPPPFE1q9f32bEds0117Bz506GDx/OqFGjeOqpp2Je7/bbb2ft2rWMHDmSYcOGcc899wDw29/+ti2NgoKCtmlvN6eddhrPP/98ymV96qmnmDJlSsrntxHJu0uubEm5Ut29W2+ZOVQXnzEwvdjLXqXj4LfHLYslm3gSBtJNujHYvSSInuGSxHpiS43XXntNv/Wtb6V8/pe//GXdsWNHxP+S8cTWOUbgzz8PJSWUr9rFkOoDqZ43z4Q6TLYH5VU6LsrI/WU9XuDpKM0SCHyZXQoFqolElEA1vuBM2S+dMoXDN77PqatWUbp+PUsnT87YVH5Cbaa21swMXHVVzs0QBJkxY8Zw4okntpsRSJTq6mquuOKKNiO7tIgk1XNlS2gEHgqCMH26FtTXa5+dO1MLguBVOhHw0gd3LuL5KC1AeOZbPgdZo6p9Wlvbzy61tqY3u5TF+AOhkeek+ybpLTOHamVJ/4jBRypL+uvNFwz1daSaUJtJIB6AHYEHj8D7Qveb8Hi95b0LIsbZnTh0MMtixOv1Kp145MWynkgksNQn5117xiAVn+P5tBqh7OWXaRo5ElzhMZsbGyl74w2YMCG1RAMSfyCb8ckTajNuY78QIaO/yZONG98U75VdLhcc8lKAu/GqofndYHN6WU8kElzqU0F+uvZMpWMSxPjfKVNbS/Fpp7Fg8mRmL1xIt+Zmmrt1Y8GsWRSvXJmWAMlW/IGgxCevIIE2k4ixn3X/nPtEGpbnypbQFPq99+q20tLIcXZLSxOP1+tVOp2BJKY5gxz3Oh2SNU4M6n1IWQXginneIcxmMnGyg0oW45MnVFcSNPZLZQrd4i/WiM1NeTnFO3awYNYsChoa6F1TQ0FDgxkJ7Nhheu6ZTCcVcs0QJYmlPiHXngVAb+czH1x7lpGAcaLruVasWEF3bR8dNzSqyhZp+SfYtKltyrZ4+3bGr11L8fbt5r/6ejNyDgKpti1nKn/GypW8M3Qwq085hcphw5ixcqXvU/kJtZmgGPslwD777MPo0aMZPnw4Z555Jrt27Yp5fHV1NUcffTRjxoxpc7faaYkk1XNlS3gZmVfLPbKxbCQBQ5TAkcJSn3w09oppnBj2XCPO7mj69yPV+5r2jIBrBN5hC8oI3Iu2VVurN18wVB+YPNCUyceRdzgxn22Cs2BJj8B37zbPds4cT5bRqqoWFha2ff/Od76j8+bNi3n80qVL9Tvf+U5S12hpaUkpb9kgmRF41oVwOltS68C9amiZbLBZtLhNi1x4eWeIiC/ZKM+1bTq2tdUTa/x0rPvT9k8Q9LrrYf4Ca5XttRW6T4MJtwD/3e9+p9///vdVVXXz5s36la98RY866ig97rjjdMOGDfqf//xHBw4cqP369dNRo0ZpQ0ODPv744zphwgQdM2aMnnPOOVrrPLvS0lK9/vrrdeLEibp06dKYx1177bU6ZswYHT58uG7YsEFVVWtra3XmzJk6fPhwHTFihP75z39WVY2ajldYAR4FrxpaxhpsrgrCoL+8vSbZUUmM57qttFTXrFjhycg7nRG0Jzr5IM8eedi2AivAVU1bmz/fzHpFGHAkLMB9bNMhAd7S0qLnnHOOPvbYY6qqetJJJ+nGjRtVVfXll1/WE088UVVV77vvPv3BD36gqqrV1dX65S9/Wevq6lRV9aabbtLrr79eVY1gvvnmmxM67vbbb1dV1bvuuktnz56tqqpz5szRyy67rC2fO3bsiJmOVwRiGZmILASmAttUdbizb39gOUYVWAGcq6o7nf9+gjHC/Ry4VFUf9ytvOYNLj9iBIOkRwwnIUp+MkEpgjRjPtbiykuKXX4YkYg1HooL0rPs9CTuaJWvxhPCwbQV6WVWvXt5Ym/to1d7Y2Mjo0aOpqKhg7NixnHrqqdTV1fHiiy/yjW98o+24PXv2dDj35ZdfZv369UycOBEwoT6POeaYtv/LHdukeMdNmzYNMNHKHnnkESBydLO///3vMdPJNH4uI1sE3An80bVvLvCkqt4kInOd31eJyDBgOnAkcBCwWkSGqmrybm5i4FVDy1iDDRmi1NdT3a8fFWVllFVUGGOggBmidCDIL2+vSHWtreu5dsCj51pG+h7+PPFP4JUA8ZoMPIO0CFC4VMDXwURBQQHr1q2jpqaGqVOnctdddzFz5kz69u0bMZKXG1Xl1FNPZenSyCaWhY4hX7zj9t13X6B9tDLVjtHN4qWTaXyzQlfVZ4EdYbvPAu53vt8PnO3av0xV96jq+8Bm4Et+5S1nKC+HLl1YOn06pZWVxl1jZSVLnf2+Wr57Qejl/atfmc98Et6QemCN0POLhEfP1Svr/mJgfArnBZ4MPIOUcVw2c/nlcMst5jNNl81pkwGr9j59+nD77bdz6623UlBQwODBg3nooYcAIzhff/31DudMmDCBF154gc1OB6KhoYGNGzemfJybSNHNUknHTzK9jOxAVf0EwPns7+wvAT50HfeRs68DInKhiKwVkbXV1XnuObuoiOonnmjz/lbTty+NPXsye+FCqp94Iv8EYq6R6qgkpGIoKtr7Uiws3Lvfo+c6A6gEVjufOesUxg8y9AySJqjhUjPU4RkzZgyjRo1i2bJlLF68mAULFjBq1CiOPPJI/vrXv3Y4vri4mEWLFjFjxgxGjhzJhAkTOoT/TOY4N5Gim6WSjp+I0Y/7lLhIGfB3lw58l6r2df2/U1X3E5G7gJdU9QFn/wJgpao+HCv9cePG6dq1a33LfxB4BThVlRrXVE5vVVaLMD572cpPkp22nD/fjI6iTcPedlvs6eO6uvxWMeQCQXsG6dapJHn11VcZO3ZsYgdHsvcI2bVEs/ewJE2kZyIir6rquPBjM+1KtUpEBqjqJyIyANjm7P8IGOg67ovA1gznLZCUAU1hephmkU4Xrcx3UjFGKy83x0QikVFJUPXDnYmgPYMgG652BruWHCOuABeR/sBEjHFZI/AWxqQ9ivIvJo8C5wM3OZ9/de1fIiL/51xnCLAmhfTzDk+sgS2xSdUYrTNZ2/tAvgRu8bQcQTeuC1qHp5MTVQcuIieKyOPAP4AzgAHAMOAa4E0RuV5Eesc4fynwEnCYiHwkIrMxgvtUEdmE8dB4E4Cqvg08CKwH/gn8wGsL9FzG6jJ9JlVjNNg7KrntNpg713xu3WqnFOOQlpvWAOF5OYJsXGcJHLFG4JOB76nqB+F/iEhXzBrvU4GIempVjSZnTo5y/I3AjTFz24nJu2hlQSLdaUs7KkmKfAkh60s57KyOJQmiCnBVvTLGfy3ACj8yZLG4ycg0ay6vt89BKsiPELIV+FQOq2u2JEjcZWQicpmI9BbDAhF5TUROy0TmLJ2bjE2z5vp6+xyjjPSdzESiGrNqI1OLS8vwpxxA/vtQsHhCIuvAZ6nqbuA0TMfyAhzdtcXiF+7pyRrnczY+vZztevuM4kcI2Wzo1PM1FG6mCYUTDW033RRdvKxYsYL169e3/b722mtZvXp12nnYtWsXd999d9vvrVu3cs4556Sdrt8ksowstIZpMnCfqr4u4f7lLBaPqSCz06wVEybQXbX99QoKqJgwwb6Q8V6V4YmbVods6tS9LEdnJeRKNRFWrFjB1KlTGTZsGAA33HCDJ3kICfCLL74YgIMOOog///nPnqTtJ4mMwF8VkScwAvxxESkCUllCZrEkTBk+Tk9Gu55dbx8Rv0a3XrlprcB09tyEOnuZIG/dzUYhU6qKuXPnMmzYMEaOHMmPf/xjXnzxRR599FGuvPJKRo8ezZYtW5g5c2aboC0rK+Pqq6/mmGOOYdy4cbz22mt85Stf4ZBDDuGee+4BoK6ujpNPPpmjjjqKESNGtHl3mzt3Llu2bGH06NFceeWVVFRUMHz4cAA+++wzLrjgAkaMGMGYMWN46qmnAFi0aBHTpk3j9NNPZ8iQIcyZM8fnOxKBSCHK3BtGyB8F9HV+HwCMjHdeJrZkw4lacotQPOvemnw861y4Xi7gSVhRn8mFPAaVpOKBa3ox5qPRpUsXHTVqVNu2bNky/fTTT3Xo0KHa2tqqqqo7d+5UVdXzzz9fH3roobZz3b9LS0v17rvvVlXVyy+/XEeMGKG7d+/Wbdu2aXFxsaqqNjc3a01NjaqaEKOHHHKItra26vvvv69HHnlkW7ru37feeqvOnDlTVVU3bNigAwcO1MbGRr3vvvt08ODBumvXLm1sbNRBgwbpBx98kPb98DScqKq2ikgVMMxZPmaxZIRMT0+mfL2gRY7ykAqCbzFunR1lBr9UFZGm0FtaWujRowff/e53mTJlClOnTk0ora9+9asAjBgxgrq6OoqKiigqKqJHjx7s2rWLwsJCrr76ap599lm6dOnCxx9/TFVVVcw0n3/+eX74wx8CcPjhh1NaWtoWwOTkk0+mT58+AAwbNozKykoGDhwYNS2vScQT281AOcbJSsi5igLP+pgviwXI/Pr3pK+XigvWCJyw6AQgeLGly8isKiNVrC7afyrIXGeua9eurFmzhieffJJly5Zx55138q9//SvueaGwoF26dGn7Hvrd0tLC4sWLqa6u5tVXX6Vbt26UlZXx2WefxUxTY8QLcV/DHYo0UyQyoj4bOExVO0ZTt1g6M6m6YM0hcml0a50d+UsZmevM1dXV0dDQwOTJk5kwYQKHOr4YioqKqHW3tySpqamhf//+dOvWjaeeeorKysq46R5//PEsXryYk046iY0bN/LBBx9w2GGH8dprr6WcD69IxIjtPUzbzXlOWHRC20jHYkmbdFyw5hDWla8F/Fs219jY2G4Z2dy5c6mtrWXq1KmMHDmSSZMm8Zvf/AaA6dOn8+tf/5oxY8awZcuWpK913nnnsXbtWsaNG8fixYs5/PDDATjggAOYOHEiw4cP58or2/swu/jii/n8888ZMWIE5eXlLFq0qN3IO5vEDScqIg8Do4AngbZRuKpe6m/W4pNsONGgTlNacpSrroJbbon+/9y5xhFHPGpr+fWl4yipauSb067NKx26JdgkFU7UIV+C0ASVZMKJJjICfxT4BfAi8Kprs1g6NyEXrJFI1AXr889DSQnlq3YxpPpAqufNg5ISs99iCSCdbdlckEnECv3+TGTEd2prmfLMJ5RUNULL/NRHOR5ZHKfai7WzCAEi3Xjgjg596ZQpzF6wgO5NTTR1786CWbOY4ZMO3dYfiyV/iCrAReRBVT1XRN7EWJ23Q1VH+pozL3Eshct7F1A1YBDV8+ZRnIKlsFcWx0sxRkHdMUYhC7B6xZwkhchRbhuMKc98QnnvgjYXro09ewIwe+FCJg4dzLJLx7Ly+AGAFbgW7wk5YmltbaVLtBCmlozSGs2mJgqxRuCXOZ+JLcBLAhH5EfBdTMfgTYx/9Z7AcsygtAI4V1V3pn0xr0Y5Hlkc50soRYtDGpGjSqoaqRowiO5NTW3CG6BbczNVAwZREmd9qsWSKqFBxJKePelfVUXJgQdaIZ5lWltbqaqqoqfrXRCPWOFEP3E+K0XkC8CXMAL3FVX9b6qZFJES4FJgmKo2isiDwHRgGPCkqt4kInOBucBVqVzDl1FOIhbHCcSEriCNtZReqQEs3pJEPPB2daxlPtXz5tHUvb0j0OZu3Sirrmb8RT/nvJkexhm39cdC+0HE/xxyCL/bsoWqrVuxAS6yT8+ePTnkkEMSPj4RRy7fBa4F/oUJbHKHiNygqgtTzqW5boGINGNG3luBnwAnOP/fDzxNigLcjWejnE2b9o64w6mvN6OvBCgjxbWUXqkBLL6Qkk1DeTnFV1zBglmzmL1wId2am2nu1o0Fs2ZRvGOHt2FMbf2xOFSwdxCxrXt3vn7EEfTGLBMcn6lM1NYaY81Ia6+LioLpQ8FpQx84baisutq002y2oUj+Vd0b8C5wgOv3AcC78c6Lk+ZlQB3mvbfY2bcr7JidUc69EFgLrB00aFB8x7L33qvbSku1oL6+va/k+nrdVlqqOn9+/DScdLSwUBU6boWFiaejKfjc3r1btahIl0yfrgX19dpn504tqK/XJeXlqkVFqrW1CV/b4j1p+Yd+7jnVoiKtLOmva8aNM3WyqMjs9wpbfywuAuM73qn7be/VwsKU6v6k+ybppPsmJX35pM7Lchsiii/0RNaBPwmcoapNzu/uwEpVPSWVDoOI7Ac8jHHPugt4CPgzcKeq9nUdt1NV94uVVkLrwJ2e3tLJkzuMcmasXJmcDtzDHmO8EVsHNcCqXRy+8f12swgFDQ28M3Qwy07ra42dskQ1JkKXWyVSgHF4kvBIvK6OWy4dS0lVI+dN+3nCOvRYdLr6k8f+6P0gpAN3e9eLZkjr68qFurqU7Ee8yF+884LUhqKtA49lhR5aH/Mx8G8R+StGB34WsCaNvJwCvK+q1c51HgGOBapEZICqfiIiA4BtaVxjL46l8IzJk5k4dHDHqY9EK0sKFsexSMbtozV2Ci4VeOAfulevtsbvqc7bIe/rj0erQzoTgfEdn4T9SDYJahuKpQMPdV+3OFuIv6Z5zQ+ACSLSE/PeOxkzJV4PnA/c5Hyme529OJbCyy4dS0lVFeMvSnGUk4bFcbJk1dipE5OsLruMYAb76DT1pxP4o/eLvPAdn6phZgLn5UQbijSv7vcGXA+8A7wF/AnYF6NbfxLY5HzuHy+dZOOBp6oryToh/Ut5uRbU12vvXbusDjMRdu82tgtz5pjP3btjHh5Vlx0nncDHEc/n+uOhbUpek2RbcJ93y8yhuviMgcmdlwkcHXrDvl2S06GnYneS5TZEFB14LCH7B2B4lP8KgVnAedHOz8TWaQS4amaMnfKJJA1kohr2vPRSQulsU9U1mgVDoETJ1/ozZ05k4R3a5s7Ndg6zT6rGYmECcltpqa6ZNMm0iWzjCFQF3davn6nT/fqZ8sUSqOkYo3nQhlKVQdEEeFQjNhEZDVwNjHBGytVAD2AIJhjNQuAezWKY0WSDmeQ8Phg75SUpGBy+ApwK1Lj29VZl9YknMv6ZZxJOJ9B4UH8C54p1/ny4/PLISzwLC+G221LWsQaurKmQqvFt2HlLp09v7wirSxdm9Ojhc+bbE25UdsnSzaz42rkdHHSdveIh7vjmoW12JW7SNkZLsw2lWqeSNmJT1XXAuSLSCxgHDMDorDeo6rtJXd3iDT4bO+UNKTjdKSOCLvvzzymrqEgqnUCTI/UnqZdcuv7oM0BWOwJJtIUOArKpngKgul+/Do6wzt/TyB1Lz6L7npqslKukqpG6ov0jOug65cknjW47ynlpGaMFrA0lEsykDuNUxWLJDVJwuhOKddxuac2DD1JcWZlUOpYM4/HqkLwjRQdUJVWNFOwxgr+irKyDwOva0sxnvb5A9z01Ec/3g3Cjslfq/hhREFcccQTnTTs/soDNpjGaD54Q4wpwS7DIdG83ENOIya7xDYX5jDatGiXMZ4elNQ0NKaUTZNJ6jkF1xerH6pCgljVZkmgL4QKSZy+H+nrKKio6CDz27cnjZ/4+e1bs5eWU3XhjZEH84YfRZ1488H6YUhvyyxNiJMV4rmzJGrFZksdrw7+kjb1SMcBxGbh02JKxGPUqnXwgU0ZwQbB69rKsfpUnUavyVOtw2HkdrK8bG70pRzo895wumTmzfb5mzvTHCj0dPPDiRrJW6G0HRLFED8KWLQEeeItjD/FSgCftcjQdAeqRm0bP0vGYjNbBTLmRDIKlvJdl9as8ydbJfLRCD1Fbqz+79Gi9/rIpuu2BBxJ/PrW1evMFQ/WByQPNUkOPO+Oh9+ak+ybpLTOHamVJ/4juvCtL+uvNFwyN+56NJsATcaX6PMbZ1CJgiaruSn287y3ZsELvVLG8a2v59aXjKKlq5JvTrk1rGjEll6PpWhh74KbR03Q8IhN1MONuJEMujyOF/U3G5XEK+FJWv8qTqlV5qnU4B1a++OVKNR3cderCB99jSPWBnLpqFTV9+7bt711Tw+pTTmFj/yru/cbBMfOStBV6CFU9TkSGYNZ9rxWRNcB9qroqmQLlA50qlrfHOpsKUnA5mm4EOK/cNAbI3WM26qBfbiR9CfubJumUNSPlSTWscap1OGBW17lCpry4JWTEpqqbROQajMvT24ExIiLA1ar6SEpXzkEq8MDvdS7guKeMOHpI0T1lGSm4HE3RGC2fqSAzdTDTbiSz6Wvaj7L6Vh6PwhrnE6l26DJmmOtn2OBI8+ruDRgJ/AbYCNwFHOXsPwiojHe+n1umdeCBCcPnA17rbCKRahhVa0S2l6zUwUy4kfQq7G+6eFVWv8pjXcfmJmnaQxBFB94lARl/J/AaMEpVf6CqrzmCfytwTepdh9wjtFa4AOOKrsD5nVejb9qPHtzsHT1EdpIQjxkYnfdq5zOu3ja0xreoyIy4wXyG9gdMF5cJslIHQxH9Vq7knaGDWX3KKVQOG2Z0uV49h/JyinfsYMGsWRQ0NNC7poaChgZvRinJ4FVZ/SpPeblZ4x6JgDiusUQgFFDrtL5s7F9F8c9+ZmYy04yWl4gRWy+gUVU/d353AXqoakNaV/aAbLlSTTZiVc4x30wjlq5f38GQp3LYMFP5MqkTDpgRWSQyvV4+K3XQb4Mmx+7iA8fuol3Y30yHBfWirH6VJ1L41JDjGhs+NdBkzJWqi9UYG5k653dP4AlMDO9OSV6E4YuFnzqbVMigEVkgHNckQFbqoN8GTV6F/fUCL8rqV3kyGNbYEmwSEeA91LhTBYxrVSeWtyVfCU0jTp7MxKGDO44e7IvC4hf5ZvXsV3kCtDLCkjheDwwSEeD1InJUSPctImNpbwSbNCLSF5gPDAcUs0TtXWA5ZlawAjhXVXemcx1LGgRpNBR08sXtZgIEfWbCSzpTWS25SSI68PHAMmCrs2sAUK6qr6Z8UZH7gedUdb6IdMdMy18N7FDVm0RkLrCfql4VK51OF040C+TKlLInpOK4Jkh6W4vFkpdE04HHFeDOyd2AwwAB3lHV5jQy0ht4HThYXRcXkXeBE1T1ExEZADytqofFSssKcP8FbKcR4I4gbmyqN1GYEjEMyqL3sFyk09SlgBJEj2WWxEjHiA1gPGZquyvGiQuq+scU83Iwxoj2PhEZBbwKXAYcqKqfADhCvH+kk0XkQuBCgEGDBqWYBUuidIpG6ziuobaWgtC+kLOMMMc1QfQeZrFYOidxBbiI/Ak4BFgHfO7sViBVAd4VOAr4oar+W0RuA+YmerKq/gH4A5gReIp5sHRywgXxJU31FADV/fpRUVZGWUUFxdu309hUzx0uQewmm97DLBaLJZER+DhgmCYy154YHwEfqeq/nd9/xgjwKhEZ4JpC3+bR9fKXTmQ85SclVY0U7Gll6fTpHafCly9v57gm0y5G8wZbV7NLqvffPrdgE8k9m3sDHgIGxDsumQ14DjjM+X4d8Gtnm+vsmwvcEi+drIQTjRKHN+MhRoMQejFfSNXtZSZcjHpJojGkvcbW1ayy7aWXdM2kSVpZ0j//wol2EkgjHvhTwE7gceDR0BbvvDhpjsYERnkDWAHsBxwAPAlscj73j5dOxgV4lLi6SzZsSC7OdbpkKj5zZ2H3bl0zaZL22bmzXQXrvWuXrpk0KaG444EXTtmKa27ralZZ0tDQ8b4nEk8gLA5Bh+fX2JjZgnRyognwRJaRTYoycn8m2dG+12TUCj1KHN7qfv0oraxs73KUOHGuUyDj8Zk7GdUvv0zpyJEdXce+8QbFEybEPjnoMZNTjSGdIrauZpfQ/W/atw9rpy2jed8200xTp0tLjX3Hvl2445uHRrTvmPLMJ1yydDMFe1ojvuO67Wlk3CPT6b6nxj63DBDNCj1uMBNHUFcA3Zzvr2CCm+QNJyw6od1LJyJR4vBWlJXRvbn9qrpQeEe/8CvYiB9UYypMdbYzEofiCRNY0KUL3fY0UlC/m4KWFhZ06RJfeEObt617v3Gw8Y4VJOENicWQ9olM1NWE2m8n5LNeX6BrS9i7qbmZirIyAAr2tEa9/yG7EHDecWHPr2tLM5/1+oL3mbYkRSJW6N/DLNvaH2ONXgLcA5zsb9YCRpQ4vGUVFTR169ZuX9w41ymQi8ZTS4HZmPjVTZioWXEjkGWRGT16cMfSs/is1xd4/MzfU9w10VWWASfDMaRzsa7mE6H7Xw2UtrS0+6+5WzfKKirMj8JCzpsW5f63zIdnL4f6evOOC3t+7NvTtBGvM29JikTCif4AmAjsBlDVTUDENdpZpbYW5s+Hq64yn5GmC9NhyJC9IS1dFG/fzoLvf5+ClpbMhXcMSujFGFRjhHcjUON8zib4I/Hue2ro/em7ST+/p2c+HdypxCh1FzD7Dz3Uv2vnQF3NV4qBBc3NHe/79u3mgFjhR11hS4u3b+/4/FparPAOApEU49re4Ozfzud/nM+uwBvxzsvE1mbElo6Bzu7desvMobr4jIGxLXPDjDrabUVFuq221lqhu1ijxqivnVGYs9+SYeLUXd8Nyfysq4m2306MtULPfUjDCv0WjJ/yd4BTgb8AN8Y7LxPb2LFj03s5JftiyZYlbzRqa/XmC4bqA5MHmqVOAbLo3abGIt/9wAo0gx0cS3uyXXf9qKsB78QGilTvf4DfMZ2JaAI8ESv0LpjZz9MwvtAfB+ZrvBMzwLhx43TtRRfB5ZdH1vEVFsJtt0UOu5eqH+u6ukDF4Q2yn+KQDrwbxi4g6DrwvCfLddfTumr90CeN9YWeu6TsC11VW4F7nS14JGGg44kfaxuHN2FmAKdgLPLL8NkuwBKfHK+71g+9xdKeRKzQ38f4Pm+Hqh7sS46SJWSgE20EHsVAJ1/8WAf95VSMFdwWg5d1NV/abyZJ9f4H/R3TmUnUF3qIHsA3MEvKgkF5OVxxReT/wqws7fIWiyV3se3XYmlPIo5cPnVtH6vqb4GT/M9aghQVmZjNRUV7l8oUFu7dH00PZpe3WCxZwRPHK7b9WiwJTaEf5frZBTMiD1Y4muOOM0YryRjoOAJ+xuTJTBw6mKoBgyirrjaNP5bgt1gs2ce235yjGmsP4zWJTKH/r+t7C+YZnOtLbtIhFQMdR/Avu3QsJVVVjL8ogH6sLRZLZGz7zRlyzStjrpCIFfqJmchI1nD8WAPZ15nV1ppZhE2bjHGejb1ryTe8ji8dpPZriYjbK2PI8/pszAoVOxJPj0Sm0KNYiBlU9f+8y07+E3Ua6fnnYfJkE1yivt7o8a+4wkwHHndcFnJqsXiMU8fLexdQNWAQ1fPmUWzreN5TgRl5u8OmhAI+WQGeHok4clkCjMfEAQc4E3gW+BBAVa9P6cIi+2Bign+sqlNFZH9gOUa2VQDnqurOWGlkNJyoB0SdRspguMdc1UNZZxI5jnW80mmpBkppL8D9CLmcz6TsyAXoBxylqrVOQtcBD6nqd9PM02XABqC383su8KSq3iQic53fV6V5jcAQcxopkXCPHjjgsHooSyaxjleCRbqd4FTPL8a8a8K9MlrhnT6JRCMbhHnfh2gizWiZIvJFYAow37X7LOB+5/v9wNnpXCNoVGAEp5u2uOEZCPeY6ehguRqjOVfzHXRyKYa9xXtmYEbcq51PO3DwhkRG4H8C1ojIXzAe2b4G/DHN6/4WmEP75WgHquonAKr6iYhEDFkqIhdi4pMzaNCgNLOROcpo3wsCV9zwFL3JJUMFOayH8trwyZIRrOMVixvrldF7EnHkciNwAbAT2AVcoKq/TPWCIjIV2Kaqr6Zyvqr+QVXHqeq44uLcqQ6haaQC6Bg33BV7twOxYvYmSm0tZQ88QFPY6KetAxFknn8eSkooX7WLIdUHUj1vnrEXeP75bOesI2nEpK8GXiH48dJTxjpeyS5OJ/jCB99Lum56cr7FHyKFKAvfgOMwghuMzBmcyHlR0voV8BFm8PdfoAF4AHgXGOAcMwB4N15abfHAc4htqpHjhvsV7tGV7pLyci2or9feu3ZpQUuLLkkv5eh4FaPZCRW7ZPp0Laiv1z47d2pBfb0uKS/3J451OvlO4/ktURNqtY/z6dtzyTY2/GdSRH1XJEu6990+t6xDGvHAfw78Ddjo/D4IeCHeeYlswAnA353vvwbmOt/nArfEOz8XBXhMamtNzN25c72JvRshVvq2fv1MIywr8ye2b5qNfdJ9k9q2W2YO1cqS/lpQX98+rnh9vVaW9NebLxjadmxW851GTPpOFzfdxpdOCM86del2gjPdibZEJJoAT0QH/jVgDPCaM2LfKiJ+KCBvAh4UkdnAB5igKZ0Lr8M9RrBuL96+neLt241u3SPr9jZqa2Hy5MhLhSZPTnqpUMYiTqWb7zRWEVSQHduErC3Ls45X4pKu45N0rf/t6oHcIREB3qSqKiIKICKFXl1cVZ8Gnna+fwqc7FXaFjJi3e51Y8+U4ZOn+U7jPpcRw7jR0impwLtOXbqdYC860daHg38kIsAfFJHfA31F5HvALOBef7Nl8YQMWLe78XzEXF5O8RVXsGDWLGYvXEi35maau3Xz3PAp7XyncZ874xpZ+yKPTRnpderS7QTb1QM5RKR59dAGCDAQOBWjo74VODXWOZnc8k4H7jVp6GZT4t57dVtpaUSd9bbSUqPzTJZMGNCkm28P7rNnBkuJ4JWRocU3Qjrw3uqRDtxtwJqKDjzV81W9s1PpxJCGEdur8Y7J1pZtAZ4TFdMv6/ZIeNDYI+K34ZMX+c7kfU4Ha1GcM+SFFbrtLHpCNAGeiC/0u4BFqvqKjxMBKZFtX+g5o9upq0suVno6OAErPnACVrSL0ZxGwArf77UX+c7kfU4F64+881JXxy2XjqWkqpHzpqUQdjWV8316F3RGovlCT0SArwcOw9hQ1GOm1VVVR/qQz6SwAjygpPuyiEBG7rUP+c42HYz1Vu3i8I3vt9P1FzQ08M7QwSw7ra+1KM5jMuoL3XYWPSXpYCYiMkhVPwDO8DVnuYp17xkdH5YKZUSg5PkSp4wty7N0Suzys8wTywp9BSYKWaWIPKyqX89QnoKPjWtsyRGsRbElRLqCMpnzbWcxQ0RSjDvT6v+J9D1IW1aM2KxnIkuu4peRocUSjh8rUvKIZA2gScETm0b53umwU0OWvKCoCFauZMbkyUwcOrijYZHVSVq8IkM+HDo7sQT4KBHZjTFaK3C+w14jtt6+5y6A2KkhS05z3HGwdSvLLh1LSVUV4y/KD2M9S8CwncWMEFWAq+o+mcxIkLF6REtekefGevlCNWbpTxk56pnPdhYj46EBdNx44JYwbFxji8XiM0uBUowLzFLnd07idBbv/cbBJqBPZxfezz8PJSWUr9rFkOoDqZ43D0pKzP4USMQXusWNnRqy5AHWPiO4pBuNzJIcGfPn4XG0RrACPDXs1JDFYvGJCrITYtYvkhWMOa86cOG3AXTGp9BFZKCIPCUiG0TkbRG5zNm/v4isEpFNzud+mc5bUtipIUsAOGHRCe1eEpbcp4zOG2I2b1QHEXAbQLvZawDdGOXM6GRjBN4C/D9VfU1EioBXRWQVMBN4UlVvEpG5wFzgqizkz2KxWLJGZwwxC1lSHfjsUdNvA+iMj8BV9RNVfc35XgtsAEqAs4D7ncPuB87OdN6S5emZT1tdYkCoBl5xPi2WXGcGUAmsdj5nZDc7GaECozpwE1Id+ILHBmVx8cEAOqs6cBEpA8YA/wYOVNVPwAh5Eekf5ZwLgQsBBg0alKGcZg4bICV5lmJ66t0xU48L6BwvPOuPPzNkq00Wk/+jbjdlZFB14INBWVx8MICOG43ML0SkF/AMcKOqPiIiu1S1r+v/naoaUw+e7WhkfmAFeHJUY3Rlbu1RAWbUktcvvwyHauzM9bIzlz3ThDrjbtWBV53xwETmSyHqYdLRyPxERLoBDwOLVfURZ3eViAxwRt8DgG3ZyFunorbWxK/etAmGDMnJEVwF+WWxmxDZGD1YLBlgBkbnXYG/VuhZ9ajpoSOljAtwERFMx2qDqv6f669HgfOBm5zPv2Y6b1knk1OizgiO1laor4fCQsjBiGpldA6LXeuPP0tYNUXG8Ut1kI8eNbPhiW0i8G3gJBFZ52yTMYL7VBHZhFlFcFMW8pY9MmlQ4YzgqK01whvMZ2h/XZ331/SJkMVuAdDb+fTDYjdIy7X8WI4SE0eIXfjgezB/vqknnQGnTV6ydDPffOxDqufN45Uzz6T65ZeznTNLumTZo6ZnBtCRQpTlyuZ3ONFkQ76lTKZDlN57r2phoSp03AoLczLU3zZVXeN8+kHG6kIiZDJU43PPqRYVaWVJf10zbpxJv6jI7M8QWbn3TpsMtYsObbOx0fNLBqqOdQYCULcThRTCiVp8JKtTops27R15h1NfD5s3p3+NBPHKQKhTWexmKlRjJ9O1h7fJS5rqKQCq+/Xr0DbP39PIHUvPovuempxTU+S7UV7C5csDj5pWgAeAjBtUDBlidN6RhHhhIRx6qLfXy3WCpgf10R+/1bUbSqoaKdjTCkBFWVmHttm1pZnPen2B7ntqspVFixfkeGQ+K8CjkeMeemJSXm4M1iLRpYuNqObGMfYrd5ZrVc+bR3EQjP0yMHrIqqVuiAx2nsLbJM9eDvX1lFVUdGib7NuTx8/8vXezPkHrJFpyg0jz6rmy+aYDd3QjDft2UQXdVlqqayZN0m0vveTP9UI68PJyLaiv1967dvmrA1fVbS+9ZMpUWrpX951p/c/u3XrLzKG6+IyBRi+/e3fmrp0ImbZNSAFf9aaZ1LVHIps6ynAdeHjb9FIHnslyBr3NpUuelo8oOvCsC+F0Nl8EeBaMV1Q1o414iaoWqGqf1lYtaG7WJUuWmJdxJgVSQA1IQgJx0n2T9JaZQ7WypH9EAVZZ0l9vvmBo1g2PfL1+FjqWHa6dzc5TJjrymSxnQNucZwS9fLt3m07FnDlJdy6iCfCseWLzgoie2FJwTtLBeGXpZgr2tFLdrx+llZXtpw/3NDLuken+GK+k4KEnWQLhuay2FkpKIhtHrVyZVeMod1248MH3GFJ9IKeuWkVN375t+3vX1LD6lFPY2L/KRKMj/3TAbWTQ41tgPGW58aFNZqWcAW5znhD08kXyu9GlC9VPPEHFhAlxndYEyhObb0RxTpLoTYIsG69kwKCigux4LssV46h8dPaQFlmy1A2E/h18b5N+ljNX2lyq5Ez53H43QtTXs3T6dGaPHEl3VZpEUnIbmz8CPI2blFXjlQxTRvY9lwXm5RyPTC3XCjoZstTtLJ2nbJQzZ9pcigS6fMuXm0Gli3ZLE519KYVOjTSvnitbOx14BOck2/r166i/1DjOPjJpvJIlQjrw3s7nkkxnINvGUckQdL1ahsi4rj+b+vdMkqly5lKbS4Ugl2/OHA13mLVm3Djts3Nnu7z2VuOMKhLkvRGbBzepjUxboWcBvz2XxSTXXs61tXrzBUP1gckDM2/s15npLJ2nTJQz19pcsgS5fB4MLvNfgHs1Ag9hX9r+kmMv52xbm3daOks7zEQ5c6zNJU1Qyxc2q9thdre1Ne5MaDQBno1gJv5QXm6ckLgo3r59r7N61eQCXTh6v3u/cTDMnp3bFppBJGQcdVpfNvavovhnPzOWojkUCc2SATpLO8xEOfO9zQW1fI7nRIqKjGE1QGEhM1aupPKNN1gtQiWpxT3PHyO20E0Ks0KfsXIlp7zxRsJW6JYMkkNuDHPFMtdiiUkOtbmUCGr5nM4Fy5ebWBOHHmqMZHv1Sksm5Y8AB89vkn1pWyzZp7O0w85Szk5Lr15mdsVDAufIRUROB24D9gHmq2rUuOARHblYLBaLxZJHRHPkEigduIjsA9wFnAEMA2aIyLDs5spisVgsluARKAEOfAnYrKrvqWoTsAw4K8t5slgsFoslcARNgJcAH7p+f+Tsa0NELhSRtSKytrq6OqOZs1gsFoslKATNiE0i7GunpFfVPwB/ABCRahGpB7ZnIG+ZoB/5URZbjmCRL+WA/CmLLUewCHo5SiPtDJoA/wgY6Pr9RWBrtINVtVhE1kZS7uci+VIWW45gkS/lgPwpiy1HsMjVcgRtCv0VYIiIDBaR7sB04NEs58lisVgslsARqBG4qraIyCXA45hlZAtV9e0sZ8tisVgslsARKAEOoKorgZVJnPIHv/KSBfKlLLYcwSJfygH5UxZbjmCRk+UInCMXi8VisVgs8QmaDtxisVgsFksCWAFusVgsFksOktMCXEROF5F3RWSziMzNdn4SRUQGishTIrJBRN4Wkcuc/deJyMciss7ZJmc7r/EQkQoRedPJ71pn3/4iskpENjmf+2U7n/EQkcNc932diOwWkctz4ZmIyEIR2SYib7n2RX0GIvITp828KyJfyU6uOxKlHL8WkXdE5A0R+YuI9HX2l4lIo+u53JO1jIcRpRxR61FQnwdELctyVzkqRGSdsz/IzyTaOzfn2kk7IgUJz4UNY6W+BTgY6A68DgzLdr4SzPsA4CjnexGwEeP7/Trgx9nOX5JlqQD6he27BZjrfJ8L3JztfCZZpn2A/2KcJwT+mQDHA0cBb8V7Bk49ex3YFxjstKF9sl2GGOU4DejqfL/ZVY4y93FB2qKUI2I9CvLziFaWsP//F7g2B55JtHduzrUT95bLI/Cc9Zuuqp+o6mvO91pgA2EuY3Ocs4D7ne/3A2dnLyspcTKwRVUrs52RRFDVZ4EdYbujPYOzgGWqukdV3wc2Y9pS1olUDlV9QlVbnJ8vY5w7BZoozyMagX0eELssIiLAucDSjGYqBWK8c3OunbjJZQEe1296LiAiZcAY4N/Orkuc6cKFuTD1jHF1+4SIvCoiFzr7DlTVT8A0HKB/1nKXGtNp/1LKtWcC0Z9BLrebWcBjrt+DReQ/IvKMiHw5W5lKgkj1KJefx5eBKlXd5NoX+GcS9s7N6XaSywI8rt/0oCMivYCHgctVdTfwO+AQYDTwCWZ6KuhMVNWjMCFgfyAix2c7Q+ngeAD8KvCQsysXn0kscrLdiMhPgRZgsbPrE2CQqo4BrgCWiEjvbOUvAaLVo5x8Hg4zaN/RDfwzifDOjXpohH2Bey65LMCT8pseNESkG6YiLVbVRwBUtUpVP1fVVuBeAjhlE46qbnU+twF/weS5SkQGADif27KXw6Q5A3hNVasgN5+JQ7RnkHPtRkTOB6YC56mjoHSmNj91vr+K0VEOzV4uYxOjHuXc8wAQka7ANGB5aF/Qn0mkdy453k5yWYDnrN90R3e0ANigqv/n2j/AddjXgLfCzw0SIlIoIkWh7xiDo7cwz+F857Dzgb9mJ4cp0W5UkWvPxEW0Z/AoMF1E9hWRwcAQYE0W8pcQInI6cBXwVVVtcO0vFpF9nO8HY8rxXnZyGZ8Y9SinnoeLU4B3VPWj0I4gP5No71xyvZ1k24ounQ2YjLEm3AL8NNv5SSLfx2GmY94A1jnbZOBPwJvO/keBAdnOa5xyHIyx1HwdeDv0DIADgCeBTc7n/tnOa4Ll6Ql8CvRx7Qv8M8F0OD4BmjEjh9mxngHwU6fNvAucke38xynHZowuMtRO7nGO/bpT514HXgPOzHb+45Qjaj0K6vOIVhZn/yLgorBjg/xMor1zc66duDfrStVisVgslhwkl6fQLRaLxWLptFgBbrFYLBZLDmIFuMVisVgsOYgV4BaLxWKx5CBWgFssFovFkoNYAW6xBBwROcAV4em/rqhWdSJyt0/XvFxEvuNH2nGuO1NE7oxzzFQRuT5TebJYgopdRmax5BAich1Qp6q3+niNrph1vEfp3kAiGUFEZgLjVPWSGMcIJn8T1eXcxWLpbNgRuMWSo4jICSLyd+f7dSJyv4g84cRoniYit4iJ1f5Px40kIjLWCTTxqog8HuYhLMRJGHeyLc45l4rIeicQxzJn35dE5EUncMWLInKYs3+miKwQkb+JyPsicomIXOEc97KI7O8c97SI/NY59y0R6eCi1vHs9bCIvOJsEwHUjDqexrhXtVg6LVaAWyz5wyHAFEwoxAeAp1R1BNAITHGE+B3AOao6FlgI3BghnYnAq67fc4ExqjoSuMjZ9w5wvJrAFdcCv3QdPxz4Jsbf941Ag3PcS4B7Wr5QVY8FLnbyEs5twG9UdTzGy9d8139rMdGwLJZOS9dsZ8BisXjGY6raLCJvAvsA/3T2vwmUAYdhhOsqMwvNPhg3meEMwMRLDvEGsFhEVgArnH19gPtFZAjGRWU31/FPqYm5XCsiNcDfXPkY6TpuKZiY0yLSW0T6huXjFGCYk1eA3iJS5KS9DTgo6p2wWDoBVoBbLPnDHgBVbRWRZt1r4NKKaesCvK2qx8RJpxHo4fo9BTgeE2b1ZyJyJPALjKD+mhNf+enwfLiuvcf13f3OCTfACf/dBThGVRsj5LGHk0+LpdNip9Atls7Du0CxiBwDJryiI4zD2QAc6hzTBRioqk8Bc4C+QC/MCPxj5/iZKean3LnGcUCNqtaE/f8E0GbMJiKjXf8NJXciw1ksvmAFuMXSSVDVJuAc4GYReR0TkenYCIc+hhlxg5lmf8CZlv8PRie9C7gF+JWIvOAckwo7ReRF4B5MxK5wLgXGOcZz69mrfwc4EfhHite1WPICu4zMYrF0QET+AsxR1U0+pf808GNVXZvCuQcCS1T1ZM8zZrHkEHYEbrFYIjEXY8wWRAYB/y/bmbBYso0dgVssFovFkoPYEbjFYrFYLDmIFeAWi8ViseQgVoBbLBaLxZKDWAFusVgsFksOYgW4xWKxWCw5yP8Hc5vn3PT9YU8AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "====== Reference: Original; Estimation: Coding ======\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "====== Reference: Original; Estimation: Talking ======\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def match_binary_matrices_tol(C_ref, C_est, tol_freq=0, tol_time=0):\n", " \"\"\"| Compare binary matrices with tolerance\n", " | Note: The tolerance parameters should be smaller than the minimum distance of\n", " peaks (1-entries in C_ref ad C_est) to obtain meaningful TP, FN, FP values\n", "\n", " Notebook: C7/C7S1_AudioIdentification.ipynb\n", "\n", " Args:\n", " C_ref (np.ndarray): Binary matrix used as reference\n", " C_est (np.ndarray): Binary matrix used as estimation\n", " tol_freq (int): Tolerance in frequency direction (vertical) (Default value = 0)\n", " tol_time (int): Tolerance in time direction (horizontal) (Default value = 0)\n", "\n", " Returns:\n", " TP (int): True positives\n", " FN (int): False negatives\n", " FP (int): False positives\n", " C_AND (np.ndarray): Boolean mask of AND of C_ref and C_est (with tolerance)\n", " \"\"\"\n", " assert C_ref.shape == C_est.shape, \"Dimensions need to agree\"\n", " N = np.sum(C_ref)\n", " M = np.sum(C_est)\n", " # Expand C_est with 2D-max-filter using the tolerance parameters\n", " C_est_max = ndimage.maximum_filter(C_est, size=(2*tol_freq+1, 2*tol_time+1),\n", " mode='constant')\n", " C_AND = np.logical_and(C_est_max, C_ref)\n", " TP = np.sum(C_AND)\n", " FN = N - TP\n", " FP = M - TP\n", " return TP, FN, FP, C_AND\n", "\n", "def compare_constellation_maps(fn_wav_D, fn_wav_Q, dist_freq = 11, dist_time = 5, \n", " tol_freq = 1, tol_time = 1):\n", " Y_D = compute_spectrogram(fn_wav_D)\n", " Cmap_D = compute_constellation_map(Y_D, dist_freq, dist_time)\n", " Y_Q = compute_spectrogram(fn_wav_Q)\n", " Cmap_Q = compute_constellation_map(Y_Q, dist_freq, dist_time)\n", "\n", " TP, FN, FP, Cmap_AND = match_binary_matrices_tol(Cmap_D, Cmap_Q, \n", " tol_freq=tol_freq, tol_time=tol_time)\n", " title=r'Matching result (tol_freq=%d and tol_time=%d): TP=%d, FN=%d, FP=%d' % \\\n", " (tol_freq,tol_time, TP, FN, FP)\n", " fig, ax, im = plot_constellation_map(Cmap_AND, color='green', s=200, marker='+', title=title)\n", " n, k = np.argwhere(Cmap_D == 1).T\n", " ax.scatter(k, n, color='r', s=50, marker='o')\n", " n, k = np.argwhere(Cmap_Q == 1).T\n", " ax.scatter(k, n, color='cyan', s=20, marker='o')\n", " plt.legend(['Matches (TP)', 'Reference', 'Estimation'], loc='upper right', framealpha=1)\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "\n", "fn_wav_D = wav_dict['Original'][-1]\n", "fn_wav_Q = wav_dict['Noise'][-1]\n", "tol_freq = 0\n", "tol_time = 0\n", "print('====== Reference: Original; Estimation: Noise ======')\n", "compare_constellation_maps(fn_wav_D, fn_wav_Q, tol_freq=tol_freq, tol_time=tol_time)\n", "\n", "tol_freq = 1\n", "tol_time = 1\n", "print('====== Reference: Original; Estimation: Noise ======')\n", "compare_constellation_maps(fn_wav_D, fn_wav_Q, tol_freq=tol_freq, tol_time=tol_time)\n", "\n", "fn_wav_Q = wav_dict['Coding'][-1]\n", "tol_freq = 1\n", "tol_time = 1\n", "print('====== Reference: Original; Estimation: Coding ======')\n", "compare_constellation_maps(fn_wav_D, fn_wav_Q, tol_freq=tol_freq, tol_time=tol_time)\n", "\n", "fn_wav_Q = wav_dict['Talking'][-1]\n", "tol_freq = 1\n", "tol_time = 1\n", "print('====== Reference: Original; Estimation: Talking ======')\n", "compare_constellation_maps(fn_wav_D, fn_wav_Q, tol_freq=tol_freq, tol_time=tol_time)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Matching Function\n", " \n", "Let us consider a short query audio fragment, called $\\mathcal{Q}$, as well as a database recording, called $\\mathcal{D}$. Furthermore, let $\\mathcal{C}(\\mathcal{Q})$ and $\\mathcal{C}(\\mathcal{D})$ denote the constellation maps of $\\mathcal{Q}$ and $\\mathcal{D}$, respectively. In the case that the query $\\mathcal{Q}$ is contained in the recording $\\mathcal{D}$, the constellation map $\\mathcal{C}(\\mathcal{Q})$ should more or less agree with the corresponding section within the constellation map $\\mathcal{C}(\\mathcal{D})$. Intuitively, the basic idea of audio identification is to put the constellation map of $\\mathcal{D}$ on a strip chart and the constellation map of $\\mathcal{Q}$ on a transparent piece of plastic. The latter is then shifted over the former, and when the number of matching points is significant, the query is considered to be contained in the document. The proper time offset of the matching position within $\\mathcal{C}(\\mathcal{D})$ is given by the shift. \n", "\n", "We now formalize the outlined matching procedure. Recall that a peak position is specified by its coordinates $(n,k)$ consisting of a time stamp $n\\in\\mathbb{Z}$ and a frequency stamp $k\\in[0:K]$. A constellation map is then a finite set of such coordinates. As before, let $\\mathcal{C}(\\mathcal{Q})\\subset \\mathbb{Z}\\times[0:K]$ and $\\mathcal{C}(\\mathcal{D})\\subset \\mathbb{Z}\\times[0:K]$ be the constellation maps of the query $\\mathcal{Q}$ and the document $\\mathcal{D}$, respectively. Shifting the query by $m\\in\\mathbb{Z}$ positions yields the constellation map $m+\\mathcal{C}(\\mathcal{Q})$ defined by\n", "\n", "\\begin{equation}\n", " m+\\mathcal{C}(\\mathcal{Q}) := \\left\\{(m+n,k) \\mid (n,k)\\in \\mathcal{C}(\\mathcal{Q}) \\right\\}.\n", "\\end{equation}\n", "\n", "To count the matching peak coordinates between a shifted query and a database document, \n", "we simply need to intersect the corresponding constellation maps and to determine the size of the resulting set. This yields a matching function $\\Delta_\\mathcal{C}:\\mathbb{Z}\\to\\mathbb{N}_0$ defined by \n", "\n", "\\begin{equation}\n", " \\Delta_\\mathcal{C}(m):= \\big| (m+\\mathcal{C}(\\mathcal{Q}))\\cap \\mathcal{C}(\\mathcal{D}) \\big|\n", "\\end{equation}\n", "\n", "for $m\\in\\mathbb{Z}$. In general, when the query and the database documents are unrelated,\n", "the number $\\Delta_\\mathcal{C}(m)$ of (coincidentally) matching peak positions is usually small compared with $|\\mathcal{C}(\\mathcal{Q})|$. Only if the query is contained in the database document will the matching function have a large value $\\Delta_\\mathcal{C}(m)$ for some shift index $m\\in\\mathbb{Z}$. This index indicates the time offset between the query $\\mathcal{Q}$ and the matching section in $\\mathcal{D}$.\n", "\n", "\n", "\n", "In the next code cell, we provide an implementation for a generalized matching function $\\Delta_\\mathcal{C}$ that also allows for small deviations (specified by tolerance parameters `tol_freq` and `tol_time`). As for the implementation, please note the following:\n", "\n", "* When computing $\\Delta_\\mathcal{C}(m)$, the shifted query $m+\\mathcal{C}(\\mathcal{Q})$ is compared with $\\mathcal{C}(\\mathcal{D})$. This is equivalent to cutting out a section of $\\mathcal{C}(\\mathcal{D})$ starting at position $m$ with the same length as the query and to compare this section with $\\mathcal{C}(\\mathcal{Q})$.\n", "\n", "* When comparing the constellation maps of $\\mathcal{Q}$ and $\\mathcal{D}$, we are interested in the number of matching peaks. This corresponds to the number of true positives (TP), when regarding $\\mathcal{D}$ as reference and $\\mathcal{Q}$ as estimation.\n", "\n", "* In the comparison, we use the function `match_binary_matrices_tol`, which has the two tolerance parameters `tol_freq` and `tol_time`. Setting these parameters to the value $0$ yields the matching function $\\Delta_\\mathcal{C}$ as introduced above.\n", "\n", "We continue with our Beatles example using `Original` as $\\mathcal{D}$ and the segment $[100:149]$ (given in samples) of `Noise` as $\\mathcal{Q}$. The following figure shows matching functions for different tolerance parameters. Note that these functions assume their maximum at the shift position $m=100$." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:52.629353Z", "iopub.status.busy": "2024-02-15T08:39:52.629159Z", "iopub.status.idle": "2024-02-15T08:39:52.846323Z", "shell.execute_reply": "2024-02-15T08:39:52.845785Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def compute_matching_function(C_D, C_Q, tol_freq=1, tol_time=1):\n", " \"\"\"Computes matching function for constellation maps\n", "\n", " Notebook: C7/C7S1_AudioIdentification.ipynb\n", "\n", " Args:\n", " C_D (np.ndarray): Binary matrix used as dababase document\n", " C_Q (np.ndarray): Binary matrix used as query document\n", " tol_freq (int): Tolerance in frequency direction (vertical) (Default value = 1)\n", " tol_time (int): Tolerance in time direction (horizontal) (Default value = 1)\n", "\n", " Returns:\n", " Delta (np.ndarray): Matching function\n", " shift_max (int): Optimal shift position maximizing Delta\n", " \"\"\"\n", " L = C_D.shape[1]\n", " N = C_Q.shape[1]\n", " M = L - N\n", " assert M >= 0, \"Query must be shorter than document\"\n", " Delta = np.zeros(L)\n", " for m in range(M + 1):\n", " C_D_crop = C_D[:, m:m+N]\n", " TP, FN, FP, C_AND = match_binary_matrices_tol(C_D_crop, C_Q,\n", " tol_freq=tol_freq, tol_time=tol_time)\n", " Delta[m] = TP\n", " shift_max = np.argmax(Delta)\n", " return Delta, shift_max\n", "\n", "dist_freq = 11\n", "dist_time = 5\n", "\n", "fn_wav_D = wav_dict['Original'][-1]\n", "Y_D = compute_spectrogram(fn_wav_D)\n", "Cmap_D = compute_constellation_map(Y_D, dist_freq, dist_time)\n", "\n", "fn_wav_Q = wav_dict['Noise'][-1]\n", "Y_Q = compute_spectrogram(fn_wav_Q)\n", "Y_Q = Y_Q[:, 100:150]\n", "Cmap_Q = compute_constellation_map(Y_Q, dist_freq, dist_time)\n", "\n", "Delta_0, shift_max_0 = compute_matching_function(Cmap_D, Cmap_Q, tol_freq=0, tol_time=0)\n", "Delta_1, shift_max_1 = compute_matching_function(Cmap_D, Cmap_Q, tol_freq=1, tol_time=1)\n", "Delta_2, shift_max_2 = compute_matching_function(Cmap_D, Cmap_Q, tol_freq=3, tol_time=2)\n", "\n", "y_max = Delta_2[shift_max_2] + 1\n", "fig, ax, line = libfmp.b.plot_signal(Delta_0, ylim=[0, y_max], color='g',\n", " xlabel='Shift (samples)', ylabel='Number of matching peaks', \n", " figsize=(7, 3))\n", "plt.title('Matching functions for different tolerance parameters')\n", "ax.plot(Delta_1, color='r')\n", "ax.plot(Delta_2, color='b')\n", "plt.legend(['tol_freq=0, tol_time=0', 'tol_freq=1, tol_time=1', \n", " 'tol_freq=3, tol_time=2'], loc='upper right', framealpha=1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the next code cell, we show the local matching result between the shifted query $m+\\mathcal{C}(\\mathcal{Q})$ and $\\mathcal{C}(\\mathcal{D})$ for different shift indices $m$. Note there are hardly any matching peaks for $m=0$, while there are many matching peaks for the optimal shift index $m=99$. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:52.848871Z", "iopub.status.busy": "2024-02-15T08:39:52.848676Z", "iopub.status.idle": "2024-02-15T08:39:53.219933Z", "shell.execute_reply": "2024-02-15T08:39:53.219218Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def plot_shifted_Cmap(Cmap_D, Cmap_Q, shift=0):\n", " Cmap_Q_extend = np.zeros(Cmap_D.shape) \n", " Cmap_Q_extend[:, shift:shift+Cmap_Q.shape[1]] = Cmap_Q\n", " TP, FN, FP, Cmap_AND = match_binary_matrices_tol(Cmap_D, Cmap_Q_extend, \n", " tol_freq=1, tol_time=1)\n", " title=r'Matching result for shift index m=%d (TP=%d)' % (shift, TP)\n", " fig, ax, im = plot_constellation_map(Cmap_AND, color='green', s=200, marker='+', title=title)\n", " n, k = np.argwhere(Cmap_D == 1).T\n", " ax.scatter(k, n, color='r', s=50, marker='o')\n", " n, k = np.argwhere(Cmap_Q_extend == 1).T\n", " ax.scatter(k, n, color='cyan', s=20, marker='o')\n", " plt.legend(['Matches (TP)', 'Reference', 'Estimated'], loc='upper right', framealpha=1)\n", " plt.show()\n", " \n", "plot_shifted_Cmap(Cmap_D, Cmap_Q, shift=0) \n", "plot_shifted_Cmap(Cmap_D, Cmap_Q, shift=shift_max_1) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Matching Functions for Beatles Examples \n", "\n", "We now have a look at the matching functions obtained from different versions of the Beatles example. As before, we use `Original` as $\\mathcal{D}$ and the segment $[100:149]$ (given in samples) of other versions as $\\mathcal{Q}$. The following figure shows matching functions for the queries `Original`, `Noise`, `Coding`, and `Talking`. While one can observe a distinct maximum in the matching function at the expected matching positions for the first three queries, the `Talking` query is much harder to identify." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:53.222961Z", "iopub.status.busy": "2024-02-15T08:39:53.222707Z", "iopub.status.idle": "2024-02-15T08:39:53.494913Z", "shell.execute_reply": "2024-02-15T08:39:53.494363Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def compute_Delta(fn_wav_D, fn_wav_Q, seg_start=100, seg_end=150, dist_freq=11, \n", " dist_time=5, tol_freq=1, tol_time=1):\n", " Y_D = compute_spectrogram(fn_wav_D)\n", " Cmap_D = compute_constellation_map(Y_D, dist_freq=dist_freq, dist_time=dist_time)\n", " Y_Q = compute_spectrogram(fn_wav_Q)\n", " Y_Q = Y_Q[:, seg_start:seg_end]\n", " Cmap_Q = compute_constellation_map(Y_Q, dist_freq=dist_freq, dist_time=dist_time)\n", " Delta, shift_max = compute_matching_function(Cmap_D, Cmap_Q, \n", " tol_freq=tol_freq, tol_time=tol_time)\n", " return Delta, shift_max\n", "\n", "fn_wav_Q = wav_dict['Original'][-1] \n", "Delta_0, shift_max_0 = compute_Delta(fn_wav_D, fn_wav_Q)\n", "fn_wav_Q = wav_dict['Noise'][-1]\n", "Delta_1, shift_max_1 = compute_Delta(fn_wav_D, fn_wav_Q)\n", "fn_wav_Q = wav_dict['Coding'][-1]\n", "Delta_2, shift_max_2 = compute_Delta(fn_wav_D, fn_wav_Q)\n", "fn_wav_Q = wav_dict['Talking'][-1]\n", "Delta_3, shift_max_3 = compute_Delta(fn_wav_D, fn_wav_Q)\n", "\n", "y_max = Delta_0[shift_max_0] + 1\n", "fig, ax, line = libfmp.b.plot_signal(Delta_0, ylim=[0, y_max], color='r',\n", " xlabel='Shift (samples)', \n", " ylabel='Number of matching peaks', \n", " figsize=(8, 3))\n", "ax.plot(Delta_1, color='b')\n", "ax.plot(Delta_2, color='c')\n", "ax.plot(Delta_3, color='k', linewidth='2')\n", "plt.legend(['Orignal', 'Noise', 'Coding', 'Talking'], loc='upper right', framealpha=1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the previous example, we have seen that correct segment in the `Original` Beatles song can hardly be identified when using the segment $[100:149]$ (given in samples) of the `Talking` version. One way to increase the **discriminative power** of the query constellation map is to increase its duration (see also the discussion of specificity and granularity in the [FMP notebook on content-based audio retrieval](../C7/C7_ContentBasedAudioRetrieval.html)). To demonstrate this, we show in the subsequent figure the matching functions for queries of different lengths:\n", "\n", "* Segment $[100:149]$ (corresponding to 2.32 seconds)\n", "* Segment $[100:174]$ (corresponding to 3.48 seconds)\n", "* Segment $[100:199]$ (corresponding to 4.64 seconds)\n", "\n", "In the case of the longest query, the peak structure becomes more prominent even in the case of the strongly distorted `Talking` version." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:53.497927Z", "iopub.status.busy": "2024-02-15T08:39:53.497684Z", "iopub.status.idle": "2024-02-15T08:39:53.734492Z", "shell.execute_reply": "2024-02-15T08:39:53.733959Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fn_wav_Q = wav_dict['Talking'][-1]\n", "Delta_0, shift_max_0 = compute_Delta(fn_wav_D, fn_wav_Q)\n", "Delta_1, shift_max_1 = compute_Delta(fn_wav_D, fn_wav_Q, seg_start=100, seg_end=175)\n", "Delta_2, shift_max_2 = compute_Delta(fn_wav_D, fn_wav_Q, seg_start=100, seg_end=200)\n", "\n", "y_max = Delta_2[shift_max_2] + 1\n", "fig, ax, line = libfmp.b.plot_signal(Delta_0, ylim=[0, y_max], color='k',\n", " xlabel='Shift (samples)', \n", " ylabel='Number of matching peaks', \n", " figsize=(8, 3), linewidth=3)\n", "ax.plot(Delta_1, color='c', linewidth=2)\n", "ax.plot(Delta_2, color='r', linewidth=1)\n", "plt.legend(['[100:149]', '[100:174]', '[100:199]'], loc='upper right', framealpha=1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We close our discussion on the matching functions by considering the two versions `Faster` (time-scale modified version played about 10 percent faster) and `Higher` (pitch-shifted version). Again using `Original` as $\\mathcal{D}$ and the segment $[100:174]$ of other versions as $\\mathcal{Q}$, the subsequent figure shows the resulting matching functions. As defined above, a matching function compares constellation maps in a rather strict sense: systematic shifts in frequency and global time stretches are not accounted for. As a result, versions such as `Faster` or `Higher` cannot be identified by the techniques discussed so far." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2024-02-15T08:39:53.737173Z", "iopub.status.busy": "2024-02-15T08:39:53.736977Z", "iopub.status.idle": "2024-02-15T08:39:54.034616Z", "shell.execute_reply": "2024-02-15T08:39:54.033861Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fn_wav_Q = wav_dict['Original'][-1] \n", "Delta_0, shift_max_0 = compute_Delta(fn_wav_D, fn_wav_Q, \n", " seg_start=100, seg_end=175, tol_freq=1, tol_time=1)\n", "fn_wav_Q = wav_dict['Faster'][-1]\n", "Delta_1, shift_max_1 = compute_Delta(fn_wav_D, fn_wav_Q, \n", " seg_start=100, seg_end=175, tol_freq=0, tol_time=0)\n", "Delta_2, shift_max_1 = compute_Delta(fn_wav_D, fn_wav_Q, \n", " seg_start=100, seg_end=175, tol_freq=1, tol_time=1)\n", "fn_wav_Q = wav_dict['Higher'][-1]\n", "Delta_3, shift_max_2 = compute_Delta(fn_wav_D, fn_wav_Q, \n", " seg_start=100, seg_end=175, tol_freq=1, tol_time=1)\n", "\n", "y_max = Delta_0[shift_max_0] + 1\n", "fig, ax, line = libfmp.b.plot_signal(Delta_0, ylim=[0, y_max], color='r',\n", " xlabel='Shift (samples)', \n", " ylabel='Number of matching peaks', \n", " figsize=(8, 3))\n", "ax.plot(Delta_1, color='b')\n", "ax.plot(Delta_2, color='c')\n", "ax.plot(Delta_3, color='k', linewidth='2')\n", "plt.legend([r'Orignal (tol_freq=1, tol_time=1)', r'Faster (tol_freq=0, tol_time=0)', \n", " r'Faster (tol_freq=1, tol_time=1)', r'Higher (tol_freq=1, tol_time=1)'], loc='upper right', framealpha=1)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Indexing\n", "\n", "In the matching processes described so far, the query needs to be compared against all sections (having the same duration as the query) of all documents contained in the database. Obviously, such an exhaustive search strategy, whose run-time linearly depends on the number and sizes of the documents, is not feasible for large databases containing millions of recordings. In view of scalability, one requires search strategies that facilitate fast information access without sacrificing the accuracy of the retrieval results. Such search strategies typically use **indexing** techniques, which optimize speed and performance by cutting down the search space through suitable look-up operations. An **index** is constructed similarly to a traditional book index, which consists of a collection of alphabetically ordered **key words** (generally referred to as **hashes**). For each key word, in turn, there is a list of increasing page numbers indicating the occurrences of the given key word in the book. In our fingerprinting context, the key words (or hashes) are (suitably quantized) frequency values of peaks (or combinations thereof), whereas the page numbers correspond to time positions and document identifiers. We do not further describe the indexing steps, which is a crucial element in audio identification system. For details, we refer to Section 7.1.3 of [Müller, FMP, Springer 2015]." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Peak Pairs\n", "\n", "Even though being robust to noise and distortions, individual spectral peaks have a [low specificity](../C7/C7_ContentBasedAudioRetrieval.html) in the sense that they are not very characteristic when considered in an isolated fashion. As a result, when using individual spectral peaks and their frequency stamps as hash values, it turns out that the resulting hash lists (\"the list of page numbers\") are long and the indexing becomes slow. Therefore, one crucial step in the fingerprinting system as introduced by Wang is to increase the specificity and the number of hashes (thus reducing the length of the resulting hash lists) without sacrificing the robustness of the fingerprints. The main idea is to form fingerprint hashes by considering pairs of peaks instead of individual ones. To this end, one fixes a point $(n_0,k_0)\\in\\mathcal{C}(\\mathcal{D})$ to serve as an **anchor point** as well as a **target zone** $T_{(n_0,k_0)}\\subset\\mathbb{Z}\\times[0:K]$ associated to it. The target zone should be thought of as a small rectangular region in the time–frequency plane close to the anchor point. Then one considers pairs of points \n", "\n", "\\begin{equation}\n", " \\big((n_0,k_0),(n_1,k_1)\\big)\n", "\\end{equation}\n", "\n", "consisting of the anchor point $(n_0,k_0)$ and some target point $(n_1,k_1)\\in T_{(n_0,k_0)}\\cap\\mathcal{C}(\\mathcal{D})$. Each pair yields a triple\n", "\n", "\\begin{equation}\n", " (k_0,k_1,n_1-n_0)\n", "\\end{equation}\n", "\n", "consisting of two frequency stamps and a difference of two time stamps. The idea is to use these triples as hashes instead of single frequency stamps. \n", "\n", "\"FMP_C7_F07.png\"\n", "\n", "At the matching stage, one now counts matching triples between the shifted query and the database document instead of considering only matching frequency stamps. One can show that, even though the number of data items to be indexed increases (by considering triples instead of single frequency stamps), one gains a tremendous acceleration in the search process thanks to the much higher specificity of the triples. For further details, we refer to the original article An Industrial Strength Audio Search Algorithm. by Wang.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Further Notes\n", "\n", "In recent years, many different fingerprinting and indexing techniques have been proposed and are now being used in commercial products. In this notebook, we had a closer look at one of these techniques, which was originally developed for the [Shazam audio identification system](https://www.shazam.com/). We discussed the main ideas underlying this system, but there are many parameters that need to be adjusted in order to find a good trade-off between the various requirements including robustness, specificity, scalability, and compactness. Important aspects include \n", "\n", "* the STFT parameters (window length, hop size) that determine the temporal and spectral resolutions, \n", "* the peak-picking strategy (with its neighborhood parameters), \n", "* the size of the target zones (used to define the triplets), and \n", "* suitable data structures for hashing.\n", "\n", "Although robust to many kinds of signal distortions, the discussed fingerprinting approach is not designed for handling temporal deformations. The matching of the constellation maps as well as the time stamp differences in the peak pairs are both sensitive to relative tempo differences between the query and database document. Therefore, one needs other techniques to become invariant to time scale modifications.\n", "\n", "The fingerprints using spectral peaks are designed to be highly sensitive to a particular version of a piece of music. For example, given a multitude of different performances of a song by the same artist, the fingerprinting system is likely to pick the correct one even if they are virtually indistinguishable by the human ear. In general, audio identification systems are designed to target identification of recordings that are already present in the database. Therefore, such techniques usually do not generalize to live recordings or performances that are not part of the database. In the following notebooks, we discuss retrieval tasks and techniques that aim at identifying different versions of a given recording including different performances of the same piece, arrangements, and cover songs." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "Acknowledgment: This notebook was created by Meinard Müller and Patricio López-Serrano.\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "
\"C0\"\"C1\"\"C2\"\"C3\"\"C4\"\"C5\"\"C6\"\"C7\"\"C8\"
" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.16" } }, "nbformat": 4, "nbformat_minor": 1 }