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Silero VAD: pre-trained enterprise-grade Voice Activity Detector
DCASE2020 Challenge Task 2 baseline system
A machine learning approach to machine anomaly detection on the MIMII dataset.
Tool for generation and playback of loudspeaker test signals. Includes a real-time sweep generator.
Using swept sine impulse technique to determine total harmonic distortion
MoSQITo is a unified and modular development framework of key sound quality metrics favoring reproducible science and efficient shared scripting among engineers, teachers and researchers community.
djcaminero / MoSQITo
Forked from Eomys/MoSQIToMoSQITo is a unified and modular development framework of key sound quality metrics favoring reproducible science and efficient shared scripting among engineers, teachers and researchers community.
"djcaminero/MoSQITo-FDP" preserves the state of algorithms and functions created for the Final Degree Project (FDP) of Daniel Jiménez-Caminero Costa, "Python implementation of the tonality psychoac…
.NET DSP library with a lot of audio processing functions
Code for the paper Hybrid Spectrogram and Waveform Source Separation
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the …
Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)
Deep speaker embeddings in PyTorch, including x-vectors. Code used in this work: https://arxiv.org/abs/2007.16196
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Use Pandas DataFrame with scikit-learn Pipelines and Feature Unions
Final project for the Speaker Recognition course on Udemy, 机器之心, 深蓝学院 and 语音之家
A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources.
Anomaly detection related books, papers, videos, and toolboxes
通过阅读网上的资料代码，进行自我加工，努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯
Matlab Coding homework for Machine Learning