{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "The FMP notebooks offer a collection of educational material closely following the textbook Fundamentals of Music Processing (FMP). This is the starting website, which is opened when calling https://www.audiolabs-erlangen.de/FMP. Besides giving an overview, this website provides information on the license and the main contributors. \n", "
" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "LICENSE
). \n",
"The Python package libfmp
(i.e., the content of the directory libfmp
) is licensed under the [MIT license](https://opensource.org/licenses/MIT) (see file libfmp_LICENSE
) and is available at [GitHub](https://github.com/meinardmueller/libfmp). As for the audio material, the respective original licenses apply. This site contains material (text passages, figures) from the book Fundamentals of Music Processing. If you use code or material from this site, please give reference to this book (e.g. Figure 1.1 from [Müller, FMP, Springer 2021]). If you publish results obtained or using these Python notebooks, please consider the following references:\n",
" \n",
"\n",
"\n",
"Chapter | \n", "Title | \n", "Notions, Techniques & Algorithms | \n", "HTML | \n", "IPYNB | \n", "
\n", " | Basics | \n", "Get started; Juypter framework; Anaconda; multimedia; Python programming; visualization; audio; Numba; annotations; libfmp; MIR resources | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Overview | \n", "Overview of the notebooks (this notebook/website) | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Music Representations | \n", "Music notation; MIDI; audio signal; waveform; pitch; loudness; timbre | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Fourier Analysis of Signals | \n", "Discrete/analog signal; sinusoid; exponential; Fourier transform; Fourier representation; DFT; FFT; STFT | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Music Synchronization | \n", "Chroma feature; dynamic programming; dynamic time warping (DTW); alignment; user interface | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Music Structure Analysis | \n", "Similarity matrix; repetition; thumbnail; homogeneity; novelty; evaluation; precision; recall; F-measure; visualization; scape plot | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Chord Recognition | \n", "Harmony; music theory; chords; scales; templates; hidden Markov model (HMM); evaluation | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Tempo and Beat Tracking | \n", "Onset; novelty; tempo; tempogram; beat; periodicity; Fourier analysis; autocorrelation | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Content-Based Audio Retrieval | \n", "Identification; fingerprint; audio matching; version identification; cover song | \n", "[html] | \n", "[ipynb] | \n", "
\n", " | Musically Informed Audio Decomposition | \n", "Harmonic/percusive separation; signal reconstruction; instantaneous frequency; fundamental frequency (F0); trajectory; nonnegative matrix factorization (NMF) | \n", "[html] | \n", "[ipynb] | \n", "
\n", "The notebooks are based on results, material, and insights that have been obtained in close collaboration with different people. I would like to express my gratitude to my former and current students, collaborators, and colleagues who have influenced and supported me in creating these notebooks. Also, various people have contributed to the code examples of the notebooks; credits are given in the notebooks' acknowledgement sections. Here, I will confine myself to only mentioning the names of the main contributors in alphabetical order: \n", " \n", "
\n", "Furthermore, some of the code examples have been inspired or are based on code provided by other code collections. In particular, I want to mention the following excellent sources:\n", "
\n", "\n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |