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athena

A release version for https://github.com/athena-team/athena

chatbot

基于人工智能的对话系统

chinese_ocr

CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras

chinesetensorflowdoc

TensorFlow2中文文档

crnn.tf2

Convolutional Recurrent Neural Network(CRNN) for End-to-End Text Recognition - TensorFlow 2

crnn_ctc_tf2

fastspeech2

An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"

fastspeech2-1

Implementation of FastSpeech 2

hlp

基于深度学习的对话系统、语音识别、机器翻译和语音合成等。

keras-ctpn

keras复现场景文本检测网络CPTN: 《Detecting Text in Natural Image with Connectionist Text Proposal Network》；欢迎试用，关注，并反馈问题...

lets_ocr

A repository for OCR, which inlcudes some classical OCR algorithms Pytorch implementation such as CTPN, EAST and CRNN.

rnnt-speech-recognition

End-to-end speech recognition using RNN Transducers in Tensorflow 2.0

simplehtr

Handwritten Text Recognition (HTR) system implemented with TensorFlow.

speech-transformer

PyTorch re-implementation of Speech-Transformer

speech-transformer-tf2.0

transformer for ASR-systerm (via tensorflow2.0)

tacotron-2

DeepMind's Tacotron-2 Tensorflow implementation

tcnlp

tensorflowtts

:stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, Korean, Chinese and Easy to adapt for other languages)

text-detection-ctpn

text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network

text-detection-ocr

Chinese text detection and recognition based on CTPN + DENSENET using Keras and Tensor Flow，使用keras和tensorflow基于CTPN+Densenet实现的中文文本检测和识别

text_renderer

tf2-crnn

TF2 implementation of Text recognition CRNN

tts

:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

wavernn

wavernn-1

WaveRNN implementation

wavernn-2

WaveRNN Vocoder + TTS

wavernn-3

Pytorch implementation of waveRNN vocoder

wavernn_tf2

WIP: wavernn_tf2 vocoder using tf.data.Dataset pipeline