Popular GitHub Repositories for Audio Quality Assessment

Learn how to design, develop, deploy and iterate on production-grade ML applications.

: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.

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

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

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

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

SoftVC VITS Singing Voice Conversion

Deezer source separation library including pretrained models.

Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling

This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), artificial intelligence security, vulnerability research, exploit development, reverse engineering, and more.

GUI for a Vocal Remover that uses Deep Neural Networks.

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.

[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.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images