Awesome Large Audio Models
Collection of resources on the applications of Large Language Models (LLMs) in Audio AI.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Speechbrain | 7,166 | 5 months ago | 149 | apache-2.0 | Python | |||||
| A PyTorch-based Speech Toolkit | ||||||||||
| Awesome Large Audio Models | 207 | 8 months ago | ||||||||
| Collection of resources on the applications of Large Language Models (LLMs) in Audio AI. | ||||||||||
| Runtimespeechrecognizer | 153 | 5 months ago | 2 | mit | C++ | |||||
| Cross-platform, real-time, offline speech recognition plugin for Unreal Engine. Based on Whisper OpenAI technology, whisper.cpp. | ||||||||||
| Web Voice Processor | 147 |  | 3 | 19 | 5 months ago | 38 | July 19, 2023 | 4 | apache-2.0 | TypeScript |
| A library for real-time voice processing in web browsers | ||||||||||
| Audiototext | 132 | 5 months ago | 1 | Jupyter Notebook | ||||||
| Transcribe and translate audio to text using Whisper and DeepL. | ||||||||||
| Vid2cleantxt | 53 | 2 years ago | 2 | February 24, 2022 | apache-2.0 | Jupyter Notebook | ||||
| Python API & command-line tool to easily transcribe speech-based video files into clean text | ||||||||||
| Vocalforge | 39 | 10 months ago | 8 | July 20, 2023 | mit | Python | ||||
| Your one-stop solution for voice dataset creation | ||||||||||
| Audio Speech Tutorial | 12 | 6 months ago | mit | Jupyter Notebook | ||||||
| This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications. | ||||||||||
| Audio Pretrained Model | 11 | 4 years ago | mit | |||||||
| A collection of Audio and Speech pre-trained models. | ||||||||||
| End2endautomaticspeechrecognition | 7 | 3 years ago | Python | |||||||
| In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. | ||||||||||
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