DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Examples of how to use or integrate DeepSpeech
基于PaddlePaddle实现的语音识别，中文语音识别。项目完善，识别效果好。支持Windows，Linux下训练和预测，支持Nvidia Jetson开发板预测。
Pytorch实现的流式与非流式的自动语音识别框架，同时兼容在线和离线识别，目前支持Conformer、Squeezeformer、DeepSpeech2模型，支持多种数据增强方法。
speech to text benchmark framework
A CLI script to generate subtitle files (SRT/VTT/TXT) for any video using either DeepSpeech or Coqui
A Keras CTC implementation of Baidu's DeepSpeech for model experimentation
🎧 Automatic Speech Recognition: DeepSpeech & Seq2Seq (TensorFlow)
A testing server for a speech to text service based on coqui.ai
Golang bindings for Mozilla's DeepSpeech speech-to-text library
ASR with PyTorch
Server & client for DeepSpeech using WebSockets for real-time speech recognition in separate environments
Android Speech Recognition Service using Vosk/Kaldi and Mozilla DeepSpeech
Tooling for producing Italian model (public release available) for DeepSpeech and text corpus
Install Mozilla DeepSpeech on a Raspberry Pi 4
Traditional ASR (Signal & Cepstral Analysis, DTW, HMM) & DNNs (Custom Models + DeepSpeech) on Indian Accent Speech
An editor for speech-to-text transcripts such as AWS Transcribe and Mozilla DeepSpeech
A MXNet implementation of Baidu's DeepSpeech architecture
Add a description, image, and links to the deepspeech topic page so that developers can more easily learn about it.
To associate your repository with the deepspeech topic, visit your repo's landing page and select "manage topics."