Gold II
1,585 Elo
- #3,805 on the ladder
- +7 today · +78 this week
- Peak 1,585
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.
Neywa-Labs/mlx-audio is #3,805 on the bestofgithub Elo ladder, in Gold II, with a rating of 1,585 (+78 this week). It has 8,273 stars, 55 gained in the last week.
1,585 Elo
8,273
git clone https://github.com/Neywa-Labs/mlx-audio.gitUse Microsoft Edge's online text-to-speech service from Python WITHOUT needing Microsoft Edge
git clone https://github.com/rany2/edge-tts.gitSpeech recognition module for Python, supporting several engines and APIs, online and offline.
git clone https://github.com/Uberi/speech_recognition.gitExamples in the MLX framework
git clone https://github.com/ml-explore/mlx-examples.gitVITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
git clone https://github.com/jaywalnut310/vits.gitA fast, local neural text to speech system
git clone https://github.com/rhasspy/piper.gitMLX: An array framework for Apple silicon
brew install mlxLoading README…