Popular GitHub Repositories for Audio Tagging

中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

Instant voice cloning by MIT and MyShell. Audio foundation model.

Easily train a good VC model with voice data <= 10 mins!

Cross-platform, customizable ML solutions for live and streaming media.

? Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

SoftVC VITS Singing Voice Conversion

Deezer source separation library including pretrained models.

GUI for a Vocal Remover that uses Deep Neural Networks.

A self-hostable bookmark-everything app (links, notes and images) with AI-based automatic tagging and full text search

Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.

Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.

A self-hostable bookmark-everything app (links, notes and images) with AI-based automatic tagging and full text search

[CVPR 2023] SadTalker：Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation

Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)

A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.

A PyTorch-based Speech Toolkit

AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

Amphion (/?m?fa??n/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.

Use PEFT or Full-parameter to finetune 450+ LLMs (Qwen2.5, InternLM3, GLM4, Llama3.3, Mistral, Yi1.5, Baichuan2, DeepSeek-R1, ...) and 150+ MLLMs (Qwen2.5-VL, Qwen2-Audio, Llama3.2-Vision, Llava, InternVL2.5, MiniCPM-V-2.6, GLM4v, Xcomposer2.5, Yi-VL, DeepSeek-VL2, Phi3.5-Vision, GOT-OCR2, ...).