:zap: TensorFlowASR: Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2. Supported languages that can use characters or subwords

基于PaddlePaddle实现端到端中文语音识别，从入门到实战，超简单的入门案例，超实用的企业项目。支持当前最流行的DeepSpeech2、Conformer、Squeezeformer模型

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。

A PyTorch implementation of DeepSpeech and DeepSpeech2.

End-to-end speech recognition using TensorFlow

This repository contains the code for our upcoming paper An Investigation of End-to-End Models for Robust Speech Recognition at ICASSP 2021.

PyTorch implementation of automatic speech recognition models.

Keras(Tensorflow) implementations of Automatic Speech Recognition

End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.

Chapter 12: End-to-end Speech Recognition

No description provided.

Android App made to test DeepSpeech2 TFLite models.

While drunk or drowsy people can’t react to stimuli efficiently in the environment, thus we intend to check for a verbal response from the driver upon detecting anomalous driving patterns. IMU tracker upon detecting frequent changes in acceleration and sharp turns triggers the voice assistant, checking up on the driver’s state and takes further action to ensure his/her safety.

This repository is a customized version of DeepSpeech2 models for speech commands recognition implemented with PyTorch Lightning

No description provided.

구음장애 음성 데이터 자연어처리 서버

DeepSpeech2 Implementation

Bangla Automatic Speech Recognition

TensorFlowASR: Almost State-of-the-art Automatic Speech Recognition in Tensorflow 2. Supported languages that can use characters or subwords

Building the DeepSpeech2

flask 기반의 backend