wenet-e2e/wenet

End-to-End Speech Processing Toolkit

Facebook AI Research's Automatic Speech Recognition Toolkit

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

A PyTorch-based Speech Toolkit

Research and Production Oriented Speaker Verification, Recognition and Diarization Toolkit

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages

Port of OpenAI's Whisper model in C/C++