【语音识别】从入门到精通——最全干货大合集!

专知 2018-11-07 11:52
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【导读】语音识别领域最全入门资料、论文、代码、产品大合集!包括语音识别,语音合成,声纹识别等内容,一文在手,带你走进语音识别的世界。

作者 | 刘斌

编辑 | Xiaowen


入门学习


语音识别研究的四大前沿方

https://blog.csdn.net/haima1998/article/details/79094341


深度学习入门论文(语音识别领域)

https://blog.csdn.net/youyuyixiu/article/details/53764218


论语音识别三大关键技术 

https://blog.csdn.net/qq_34231800/article/details/80189617


深度学习与语音识别—常用声学模型简介

https://blog.csdn.net/dujiajiyi_xue5211314/article/details/53943313


有趣的开源软件:语音识别工具Kaldi 

https://blog.csdn.net/AMDS123/article/details/70313780


神经网络-CNN结构和语音识别应用 

https://blog.csdn.net/xmdxcsj/article/details/54695995


语音识别概述 

https://blog.csdn.net/shichaog/article/details/72528637


端到端语音识别 

https://blog.csdn.net/xmdxcsj/article/details/70300546


Attention在语音识别中的应用 

https://blog.csdn.net/quheDiegooo/article/details/76842201


语音合成技术 

https://blog.csdn.net/wja8a45TJ1Xa/article/details/78599509?locationNum=8&fps=1


深度学习于语音合成研究综述 

https://blog.csdn.net/weixin_37598106/article/details/81513816


端到端的TTS深度学习模型tacotron(中文语音合成) 

https://blog.csdn.net/yunnangf/article/details/79585089


TACOTRON:端到端的语音合成 

https://blog.csdn.net/Left_Think/article/details/74905928


声纹识别技术简介  

https://www.cnblogs.com/wuxian11/p/6498699.html


声纹识别技术的现状、局限与趋势 

https://blog.csdn.net/jojozhangju/article/details/78637221


声纹识别 

https://www.jianshu.com/p/513dadeef1fd


Deep speaker介绍 

https://blog.csdn.net/Lauyeed/article/details/79936632


论文


语音识别 DNN 

Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition(2012), George E. Dahl et al. 

https://ieeexplore.ieee.org/document/5740583/?part=1


Deep Neural Networks for Acoustic Modeling in Speech Recognition(2012), Geoffrey Hinton et al. 

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6296526


语音识别 CNN

Applying Convolutional Neural Networks concepts to hybrid NN-HMM model for speech recognition(2012), Ossama Abdel-Hamid et al.

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6288864


Deep convolutional neural networks for LVCSR(2013), Tara N. Sainath et al. 

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6639347


Analysis of CNN-based speech recognition system using raw speech as input(2015), Dimitri Palaz et al. 

https://infoscience.epfl.ch/record/210029/files/Palaz_INTERSPEECH_2015.pdf


Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition(2016), Yanmin Qian et al. 

https://pdfs.semanticscholar.org/8043/cbfed66c98d2255ea79254de620837478099.pdf

 

Very deep multilingual convolutional neural networks for LVCSR(2016), Tom Sercu et al. 

https://arxiv.org/pdf/1509.08967.pdf


Advances in Very Deep Convolutional Neural Networks for LVCSR(2016), Tom Sercu et al. 

https://arxiv.org/pdf/1604.01792.pdf


Deep Convolutional Neural Networks with Layer-Wise Context Expansion and Attention(2016), Dong Yu et al. 

https://pdfs.semanticscholar.org/716e/60cbbdacf01b3148e91a555358a96308b770.pdf?_ga=2.38333155.198966451.1540996486-1278087525.1535180761


语音识别 LSTM

Long short-term memory recurrent neural network architectures for large scale acoustic modeling(2014), Hasim Sak et al. 

https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/43905.pdf


Deep LSTM for Large Vocabulary Continuous Speech Recognition(2017), Xu Tian et al. 

https://arxiv.org/pdf/1703.07090.pdf


English Conversational Telephone Speech Recognition by Humans and Machines(2017), George Saon et al. 

https://arxiv.org/pdf/1703.02136.pdf



语音识别 CTC 

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks(2006), Alex Graves et al. 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.75.6306&rep=rep1&type=pdf


Towards End-to-End Speech Recognition with Recurrent Neural Networks(2014), Alex Graves et al. 

http://proceedings.mlr.press/v32/graves14.pdf


First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs(2014), Andrew L. Maas et al. 

https://arxiv.org/pdf/1408.2873.pdf


Deep Speech: Scaling up end-to-end speech recognition(2014), Awni Y. Hannun et al. 

https://arxiv.org/pdf/1412.5567.pdf


Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification(2015), Kyuyeon Hwang et al. 

https://arxiv.org/pdf/1511.06841.pdf


Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition(2015), Hasim Sak et al.  

https://arxiv.org/pdf/1507.06947.pdf


Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning(2016), Suyoun Kim et al. 

https://arxiv.org/pdf/1609.06773.pdf


Deep Speech 2: End-to-End Speech Recognition in English and Mandarin(2016), Dario Amodei et al. 

http://proceedings.mlr.press/v48/amodei16.pdf


Wav2Letter: an End-to-End ConvNet-based Speech Recognition System(2016), Ronan Collobert et al. 

https://arxiv.org/pdf/1609.03193.pdf


Multi-task Learning with CTC and Segmental CRF for Speech Recognition(2017), Liang Lu et al.

https://arxiv.org/pdf/1702.06378.pdf


Residual Convolutional CTC Networks for Automatic Speech Recognition(2017), Yisen Wang et al.`

https://arxiv.org/pdf/1702.07793.pdf


语音识别 Sequence Transduction

Sequence Transduction with Recurrent Neural Networks(2012), Alex Graves et al. 

https://arxiv.org/pdf/1211.3711.pdf


语音识别 attention

End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results(2014), Jan Chorowski et al. 

https://arxiv.org/pdf/1412.1602.pdf


Attention-Based Models for Speech Recognition(2015), Jan Chorowski et al. 

https://arxiv.org/pdf/1506.07503.pdf


End-to-end attention-based large vocabulary speech recognition(2016), Dzmitry Bahdanau et al. 

https://arxiv.org/pdf/1508.04395.pdf


Listen, attend and spell: A neural network for large vocabulary conversational speech recognition(2016), William Chan et al. 

https://arxiv.org/pdf/1508.01211.pdf


End-to-end attention-based distant speech recognition with Highway LSTM(2016), Hassan Taherian. 

https://arxiv.org/pdf/1610.05361.pdf


Direct Acoustics-to-Word Models for English Conversational Speech Recognition(2017), Kartik Audhkhasi et al. 

https://arxiv.org/pdf/1703.07754.pdf


语音识别 多通道 

Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition(2017), Tara N. Sainath et al. 

http://www.ee.columbia.edu/~ronw/pubs/taslp2017-multichannel.pdf


Multichannel End-to-end Speech Recognition(2017), Tsubasa Ochiai et al. 

https://arxiv.org/pdf/1703.04783.pdf


语音合成 SampleRNN

SampleRNN: An Unconditional End-to-End Neural Audio Generation Model(2016), Soroush Mehri et al.

https://arxiv.org/pdf/1612.07837.pdf


语音合成 WaveNet 

WaveNet: A Generative Model for Raw Audio(2016), Aäron van den Oord et al. 

https://arxiv.org/pdf/1609.03499.pdf


语音合成 Deep Voice

Deep Voice: Real-time Neural Text-to-Speech(2017), Sercan O. Arik et al. 

https://arxiv.org/pdf/1702.07825.pdf


语音合成 Deep Voice 2

Deep Voice 2: Multi-Speaker Neural Text-to-Speech(2017), Sercan Arik et al. 

https://arxiv.org/pdf/1705.08947.pdf


语音合成 Tacotron

Tacotron: Towards End-to-End Speech Synthesis(2017), Yuxuan Wang et al. 

https://pdfs.semanticscholar.org/f258/f0d3260e7fbdd961993086aaafa2afc714c9.pdf


语音合成 Tacotron 2

Natural tts synthesis by conditioning wavenet on mel spectrogram predictions(2018), Jonathan Shen et al. 

https://sigport.org/sites/default/files/docs/ICASSP%202018%20-%20Tacotron%202.pdf


语音合成 Voiceloop

Voiceloop: Voice Fitting and Synthesis via a Phonological Loop(2018), Yaniv Taigman et al. 

https://arxiv.org/pdf/1707.06588.pdf



声纹识别 x-vector 使用TDNN提取语音的embedding 

Deep Neural Network Embeddings for Text-Independent Speaker Verification(2017), David Snyder et al.

http://danielpovey.com/files/2017_interspeech_embeddings.pdf


百度 端到端声纹识别 Triplet Loss

Deep Speaker: an End-to-End Neural Speaker Embedding System(2017), Chao Li et al. 

https://arxiv.org/pdf/1705.02304.pdf


声纹识别 3D卷积网络 

Text-independent speaker verification using 3d convolutional neural networks(2018), Amirsina Torfi et al. 

https://arxiv.org/pdf/1705.09422.pdf


声纹识别 端到端 GE2E

Generalized End-to-End Loss for Speaker Verfication(2018)  Wan L et al. 

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8462665


代码


kaldi  

使用广泛的语音工具包 

https://github.com/kaldi-asr/kaldi


A TensorFlow implementation of Baidu's DeepSpeech architecture     

语音识别 Baidu DeepSpeech TensorFlow实现

https://github.com/mozilla/DeepSpeech


Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow 

语音识别 DeepMind's WaveNet TensorFlow实现

https://github.com/buriburisuri/speech-to-text-wavenet


End-to-end automatic speech recognition system implemented in TensorFlow.

端到端语音识别 TensorFlow实现

https://github.com/zzw922cn/Automatic_Speech_Recognition


A PyTorch Implementation of End-to-End Models for Speech-to-Text 

端到端语音识别 PyTorch实现

https://github.com/awni/speech


A PaddlePaddle implementation of DeepSpeech2 architecture for ASR.

语音识别 DeepSpeech2 PaddlePaddle实现

https://github.com/PaddlePaddle/DeepSpeech


A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model 

语音合成 Tacotron TensorFlow实现

https://github.com/Kyubyong/tacotron


Tacotron 2 - PyTorch implementation with faster-than-realtime inference 

语音合成 Tacotron2 PyTorch实现

https://github.com/NVIDIA/tacotron2


Deep neural networks for voice conversion (voice style transfer) in Tensorflow 

语音合成 Deep-voice TensorFlow实现

https://github.com/andabi/deep-voice-conversion


A method to generate speech across multiple speakers 

语音合成 facebook PyTorch实现

https://github.com/facebookresearch/loop


Speaker embedding(verification and recognition) using Pytorch 

声纹识别 PyTorch实现

https://github.com/qqueing/DeepSpeaker-pytorch


Deep Learning & 3D Convolutional Neural Networks for Speaker Verification 

声纹识别 3D卷积 TensorFlow实现

https://github.com/astofi/3D-convolutional-speaker-recognition


产品应用


百度语音官网 

http://yuyin.baidu.com/


腾讯AI开放平台 

https://ai.qq.com/product/aaiasr.shtml


讯飞开放平台 

https://xfyun.cn/services/voicedictation


必应语音 

https://azure.microsoft.com/zh-cn/services/cognitive-services/speech/


作者简介

刘斌,中科院自动化所博士生,研究方向为鲁棒性声学建模。


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