libtsm - a Python Library for Time-Scale Modification and Pitch-Shifting

This notebook demonstrates the functionalities of libtsm - a Python library for Time-Scale Modification (TSM) and pitch-shifting. It is based on a re-implementation of the Matlab TSM toolbox by Jonathan Driedger and Meinard Müller.

If you are using libtsm for your work, please cite:

Sebastian Rosenzweig, Simon Schwär, Jonathan Driedger, and Meinard Müller:
Adaptive Pitch-Shifting with Applications to Intonation Adjustment in A Cappella Recordings
Proceedings of the International Conference on Digital Audio Effects (DAFx), 2021.

Further contributors:

  • Edgar Suarez
  • El Mehdi Lemnaouar
  • Miguel Gonzales

In [1]:
import numpy as np
import librosa
import IPython.display as ipd
import as sio

import libtsm
In [2]:
# Choose File
#filename = 'Bongo'
#filename = 'BeethovenOrchestra'
#filename = 'BeethovenPiano'
filename = 'CastanetsViolin'
#filename = 'DrumSolo'
#filename = 'Glockenspiel'
#filename = 'Stepdad'
#filename = 'Jazz'
#filename = 'Pop'
#filename = 'SingingVoice'
#filename = 'SynthMono'
#filename = 'SynthPoly'
#filename = 'Scale_Cmajor_Piano'

directory = './data/'
audio_file = directory + filename + '.wav'
x, Fs = librosa.load(audio_file)
#x = 0.5 * np.sin(2*np.pi*440*np.arange(0, len(x)/Fs, 1/Fs))

print('Original signal', flush=True)
ipd.display(ipd.Audio(x, rate=Fs, normalize=True))
Original signal

Overlap-Add (OLA)

In [3]:
alpha = 1.8  # time-stretch factor
y_ola = libtsm.wsola_tsm(x, alpha, tol=0)

print('Original signal', flush=True)
ipd.display(ipd.Audio(x, rate=Fs, normalize=True))

print('Time-Scale modified signal with OLA', flush=True)
ipd.display(ipd.Audio(y_ola[:, 0], rate=Fs, normalize=True))
Original signal