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3d-audio

transform stereo tracks to 3D audio

3d-audio-w-hrtf

Plays any wav file with 3d positioning in a circle using a customizable HRTF. Done with python

acoustic-simulator

atfa-examples

Example algorithms for the ATFA (Real-time testing environment for adaptive filters)

audio-filter

autoeq

Automatic headphone equalization from frequency responses

cipichrtfapplication

doa-estimation-music-esprit

Direction of Arrival Estimation using MUSIC and ESPRIT Algorithms in Python

doatools.py

A simple library for theoretical research on direction-of-arrival (DOA) estimation in array signal processing.

drirlearning

Directional Room Impulse Response Machine Learning

hrtftools

Python tools to record HRTFs without any professional equipment

localizationtdoa

TDOA localization Python implementation.

music

Python implementation of the MUSIC Algorithm

pyaudioanalysis

Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

pyeq

python-vad

🔈 Use python to achieve voice activity detection, this little program may be helpful for voice application

python_speech_features

This library provides common speech features for ASR including MFCCs and filterbank energies.

rir_simulator_python

Room impulse response simulator using python

tdoa

TDOA based on GCC-PHAT

tdoachan

chans algorithm etc

tensorgcc

This is a TensorFlow implementation of the generalized cross-correlation (GCC Knapp & Carter), which can be used at any point of the graph. It implements the standard GCC, as well as the PHAT transform.

thinkdsp

Think DSP: Digital Signal Processing in Python, by Allen B. Downey.

user-authentication-using-voice-recognition-using-machine-learning

Voice Recognition is used to recognize a speaker's voice through his/her pitch and Frequency. We aim to recognize a speaker at real-time. We use two modules – feature extraction and codebook generation. We have extracted voice features by computing Mel Frequency Cepstrum Coefficients. Speaker specific codebook is generated by the Vector Quantization technique introduced by Linde, Buzo and Gray. In the training phase, speaker specific codebook is computed and stored in the database against each speaker. At the time of recognition, in- put voice signal is recorded and its codebook is computed and compared with the codebooks stored in the database. If a match is found the recognized speaker details is displayed, else error message is displayed.

voice-disciminator

A neural network for filtering target speaker's voice from audio written in tensorflow