PaddlePaddle / Deepspeech
Licence: apache-2.0
A PaddlePaddle implementation of ASR.
Stars: β 1,219
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Deepspeech
Annyang
π¬ Speech recognition for your site
Stars: β 6,216 (+409.93%)
Mutual labels: speech-recognition, speech, speech-to-text
Openasr
A pytorch based end2end speech recognition system.
Stars: β 69 (-94.34%)
Mutual labels: speech-recognition, speech, speech-to-text
simple-obs-stt
Speech-to-text and keyboard input captions for OBS.
Stars: β 89 (-92.7%)
Mutual labels: speech, speech-recognition, speech-to-text
wav2vec2-live
A live speech recognition using Facebooks wav2vec 2.0 model.
Stars: β 205 (-83.18%)
Mutual labels: speech, speech-recognition, speech-to-text
Awesome Kaldi
This is a list of features, scripts, blogs and resources for better using Kaldi ( http://kaldi-asr.org/ )
Stars: β 393 (-67.76%)
Mutual labels: speech-recognition, speech, speech-to-text
ASR-Audio-Data-Links
A list of publically available audio data that anyone can download for ASR or other speech activities
Stars: β 179 (-85.32%)
Mutual labels: speech, speech-recognition, speech-to-text
Syn Speech
Syn.Speech is a flexible speaker independent continuous speech recognition engine for Mono and .NET framework
Stars: β 57 (-95.32%)
Mutual labels: speech-recognition, speech, speech-to-text
sova-asr
SOVA ASR (Automatic Speech Recognition)
Stars: β 123 (-89.91%)
Mutual labels: speech, speech-recognition, speech-to-text
speech to text
how to use the Google Cloud Speech API to transcribe audio/video files.
Stars: β 35 (-97.13%)
Mutual labels: speech, speech-recognition, speech-to-text
anycontrol
Voice control for your websites and applications
Stars: β 53 (-95.65%)
Mutual labels: speech, speech-recognition, speech-to-text
Sonus
π¬ /so.nus/ STT (speech to text) for Node with offline hotword detection
Stars: β 532 (-56.36%)
Mutual labels: speech-recognition, speech, speech-to-text
Speechbrain.github.io
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
Stars: β 242 (-80.15%)
Mutual labels: speech-recognition, speech, speech-to-text
KeenASR-Android-PoC
A proof-of-concept app using KeenASR SDK on Android. WE ARE HIRING: https://keenresearch.com/careers.html
Stars: β 21 (-98.28%)
Mutual labels: speech, speech-recognition, speech-to-text
Edgedict
Working online speech recognition based on RNN Transducer. ( Trained model release available in release )
Stars: β 205 (-83.18%)
Mutual labels: speech-recognition, speech, speech-to-text
kaldi ag training
Docker image and scripts for training finetuned or completely personal Kaldi speech models. Particularly for use with kaldi-active-grammar.
Stars: β 14 (-98.85%)
Mutual labels: speech, speech-recognition, speech-to-text
Asr audio data links
A list of publically available audio data that anyone can download for ASR or other speech activities
Stars: β 128 (-89.5%)
Mutual labels: speech-recognition, speech, speech-to-text
Tacotron asr
Speech Recognition Using Tacotron
Stars: β 165 (-86.46%)
Mutual labels: speech-recognition, speech, speech-to-text
deepspeech.mxnet
A MXNet implementation of Baidu's DeepSpeech architecture
Stars: β 82 (-93.27%)
Mutual labels: speech, speech-recognition, speech-to-text
Java Speech Api
The J.A.R.V.I.S. Speech API is designed to be simple and efficient, using the speech engines created by Google to provide functionality for parts of the API. Essentially, it is an API written in Java, including a recognizer, synthesizer, and a microphone capture utility. The project uses Google services for the synthesizer and recognizer. While this requires an Internet connection, it provides a complete, modern, and fully functional speech API in Java.
Stars: β 490 (-59.8%)
Mutual labels: speech-recognition, speech, speech-to-text
DeepSpeech on PaddlePaddle
DeepSpeech on PaddlePaddle is an open-source implementation of end-to-end Automatic Speech Recognition (ASR) engine, with PaddlePaddle platform. Our vision is to empower both industrial application and academic research on speech recognition, via an easy-to-use, efficient and scalable implementation, including training, inference & testing module, and demo deployment.
Models
Setup
- python>=3.7
- paddlepaddle>=2.0.0
- Run the setup script for the remaining dependencies
git clone https://github.com/PaddlePaddle/DeepSpeech.git
cd DeepSpeech
pushd tools; make; popd
source tools/venv/bin/activate
bash setup.sh
- Source venv before do experiment.
source tools/venv/bin/activate
Getting Started
Please see Getting Started and tiny egs.
More Information
- Install
- Getting Started
- Data Prepration
- Data Augmentation
- Ngram LM
- Server Demo
- Benchmark
- Relased Model
- FAQ
Questions and Help
You are welcome to submit questions and bug reports in Github Issues. You are also welcome to contribute to this project.
License
DeepSpeech is provided under the Apache-2.0 License.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].