Awesome GitHub RepositoriesAudio Feature Extraction

PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic differentiation system that allows for flexible, non-static graph execution. The framework is designed for deep integration with Python, enabling natural usage alongside standard scientific computing ecosystems. It distinguishes itself through a comprehensive distributed training sui

This project is a comprehensive software suite for voice synthesis and model management, providing a framework for training custom acoustic models and performing voice conversion. It utilizes deep-learning-based acoustic modeling to map source audio characteristics to target voice identities, enabling the transformation of input audio into specific vocal profiles. The system distinguishes itself through a feature-retrieval-based inference mechanism, which employs vector index files to perform nearest-neighbor searches on acoustic features for high-fidelity timbre matching. Users can manage th

Fairseq is a PyTorch toolkit for sequence-to-sequence modeling, specializing in neural machine translation, automatic speech recognition, and large-scale language model training. It provides a framework for processing and aligning diverse data sources, including text, audio, and video, to support tasks such as speech-to-text conversion and multimodal sequence learning. The project is distinguished by its distributed training capabilities, which utilize parameter sharding, mixed-precision training, and CPU offloading to handle models that exceed single-device memory. It also includes specializ

Spleeter is an AI audio source separation library and deep learning toolkit designed to split mixed music files into individual audio stems, such as vocals and drums. It provides a suite of pretrained models for isolating different instruments and voices from a recording. The toolkit includes capabilities for training and evaluating custom audio separation models using labeled datasets and configuration files. It also features utilities for measuring model performance by comparing separation outputs against reference datasets. The system manages audio processing through spectral representati

This project is a singing voice conversion tool based on VITS generative modeling. It transforms the identity of a singing voice to a target speaker while preserving the original melody, lyrics, and intonation. The system distinguishes itself through hybrid voice synthesis, allowing for the blending of multiple speaker identities via linear model interpolation. It utilizes cluster-based feature retrieval to increase target voice similarity and employs a diffusion probabilistic model as a post-processor to remove electronic artifacts and improve vocal clarity. The software covers a broad rang

This project is a comprehensive framework and toolkit for developing, optimizing, and deploying transformer-based models across multimodal, document intelligence, and natural language processing tasks. It provides a unified neural architecture that processes text, vision, audio, and document layout data through a shared set of weights, enabling researchers and developers to build foundational models that align cross-modal representations. The platform distinguishes itself through advanced training and inference strategies designed for large-scale deep learning. It incorporates specialized mec

Magenta is a comprehensive toolkit for training, synthesizing, and performing music through neural models and hardware-integrated engines. It functions as a machine learning framework that enables the generation, manipulation, and real-time performance of audio, providing the structural foundations for musical intelligence through hierarchical sequence modeling and symbolic processing. The project distinguishes itself by enabling real-time, low-latency neural audio synthesis that can be integrated directly into professional digital audio workstations. It supports interactive musical jamming a

Vosk is an offline speech-to-text engine and API that converts spoken audio into text locally on a device. It provides a cross-platform speech toolkit with language bindings for integrating voice recognition into server environments, Android, iOS, and Raspberry Pi. The project includes a speaker identification tool to distinguish between different voices and an acoustic model trainer for building custom neural network models. These training tools enable speech feature extraction and model accuracy evaluation to improve recognition for specialized domains. The system supports real-time audio

Tortoise-tts is a neural text-to-speech engine and voice cloning toolkit designed for high-quality audio generation. It functions as a zero-shot synthesis system, meaning it can generate speech for unseen speakers without requiring additional training or fine-tuning for each new voice. The system specializes in replicating human vocal characteristics using small sets of reference audio clips. It allows for the extraction of voice latents to mimic specific speakers, the generation of random synthetic identities, and the blending of multiple voice profiles to create hybrid vocal identities. Th

Duix-Avatar is an AI digital human toolkit used to create, clone, and animate realistic virtual personas. It functions as a digital persona cloning tool and a text-to-speech animation API that converts written text or audio into synthetic voice and facial motion markers. The framework provides an offline video generation engine that renders digital human animations and lip-synced videos on local hardware. It includes a specialized lip sync engine to synchronize mouth movements with audio waveforms and a pipeline for extracting facial and vocal features from source media to create synthetic re

PaddleSpeech is a comprehensive toolkit of neural models for speech recognition, synthesis, and translation built on the PaddlePaddle deep learning framework. It provides a collection of frameworks and tools for converting spoken audio into written text, synthesizing natural audio from text, and performing direct speech translation. The toolkit includes specialized capabilities for keyword spotting to detect trigger words and speaker verification systems that extract unique voiceprints to identify and distinguish between individuals. It also features end-to-end translation tools that map audi

AudioKit is an audio framework for iOS, macOS, and tvOS that provides tools for digital audio synthesis, signal processing, and audio analysis. It functions as a synthesis engine for generating audio waveforms and textures, a processing library for modifying tonal characteristics, and a toolkit for extracting frequency and amplitude data from sonic signals. The framework utilizes a modular node architecture and graph-based signal routing to connect audio generators, processors, and outputs. It wraps low-level audio primitives in high-level classes to facilitate sound generation and modificati

Demucs is a deep learning stem splitter and AI music de-mixing software used to isolate vocals and instruments from a single audio file. It functions as a PyTorch audio source separation tool that splits mixed tracks into individual stems such as drums, bass, and vocals. The system is a hybrid spectrogram waveform separator that combines spectral and waveform analysis. This approach allows the software to process audio in both frequency and time domains to achieve high-fidelity source separation. The tool provides capabilities for audio source separation, including acapella track extraction

This project is an AI singing voice conversion system and vocal processor used for training generative voice models and converting vocal recordings or live input into a target voice. It functions as a VITS model trainer and a real-time voice changer that transforms vocal timbre and pitch to change the identity of a singer. The system provides a graphical management dashboard for controlling training hyperparameters and voice conversion presets. It supports low-latency audio streaming for live microphone input and employs pitch estimation to ensure precise matching between source and target vo

Pyannote.audio is a PyTorch toolkit for speaker diarization, speaker identification, and speech activity detection. Its primary purpose is to partition audio recordings into segments and assign each segment to a specific speaker identity to determine who spoke when. The project includes a framework for classifying speaker identities and a pipeline for distinguishing human speech from background noise. It provides specialized tools for handling symmetric-overlap speech, where multiple speakers talk simultaneously, and employs learnable band-pass filters for raw waveform feature extraction. Th

This project is a Chinese automatic speech recognition framework and deep learning system designed to convert spoken Chinese audio into written text. It functions as a toolkit for training, evaluating, and deploying speech-to-text models, utilizing a specialized pinyin-to-text converter that transforms phonetic sequences into Chinese characters using a probability graph model. The system is distinguished by its deployment flexibility, offering a dockerized recognition server that provides transcription capabilities as a remote API. It supports high-performance streaming through a gRPC speech-

Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature extraction suite and music information retrieval tool designed to analyze the structural and sonic characteristics of audio signals. The library provides specialized capabilities for music analysis, including dynamic tempo tracking to identify rhythmic pulses and spectral feature extraction to compute harmonic spectra, chroma variants, and onset points. It also serves as a time-series audio processor for synchronizing audio streams. The system covers a broad range of audio processing

THIS REPO IS NOT MAINTAINED ANYMORE. Please see https://codeberg.org/tenacityteam/tenacity for Tenacity, which is maintained.

This is a tool for downloading videos, images, and audio from the Douyin social media platform using shareable URLs or profile links. It can download individual posts, entire user profiles including all posts and liked content, collections, and music tracks, with options for watermark-free and high-quality output. The tool also supports live stream recording, comment collection, and keyword-based content search with JSONL export. The project distinguishes itself through an integrated REST API server that accepts download and transcription requests, tracks job status, and exposes health check