Reading list from NCMMSC Speech group

|Paper||Referee||Area and notes||Link |- |George E. Dahl, Dong Yu, Li Deng, and Alex Acero, Context-Dependent |- Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition, |- 2011, IEEE Trans on ASLP. Vol.20, No.1.||贾磊（百度）||推动DNN应用于工业级ASR |- http://research.microsoft.com/pubs/144412/dbn4lvcsr-transaslp.pdf |- |Lawrence R. Rabiner, A tutorial on hidden Markov models and selected |- applications in speech recognition||谢磊（西工大）||HMM |- http://www.cs.ubc.ca/~murphyk/Bayes/rabiner.pdf |- |End-to-End Text-Dependent Speaker Verification Georg Heigold, Ignacio Moreno, |- Samy Bengio, Noam Shazeer||肖雄（南洋理工大学） |- 这篇文章用神经网络来对不同长度的句子提取固定长度的向量（类似ivector）的作用。 |- 下载地址：http://arxiv.org/abs/1509.08062。 |- |Rapid Speaker Adaptation in Eigenvoice Space||苏腾荣（华米） |- 对后面的基于超矢量的方法都有影响 |- http://courses.cs.tamu.edu/rgutier/cpsc689_s07/kuhn2000speakerAdaptationEigenvoice.pdf |- |G. Hinton, L. Deng, D. Yu et al., “Deep neural networks for acoustic modeling |- in speech recognition: The shared views of four research groups,” Signal |- Processing Magazine, IEEE, vol. 29, no. 6, pp. 82-97, 2012. |- 邹月娴（北大深圳）||DNN 声学模型|| |- |Speech recognition with weighted finite-state transducers||苏腾荣（华米） |- ASR的标配||http://www.cslu.ogi.edu/~zak/cs506-lvr/mohri-wfst_asr.pdf |- |Speech Recognition Algorithms Using Weighted Finite-State Transducers Takaaki |- Hori and Atsushi Nakamura Synthesis Lectures on Speech and Audio |- Processing, January 2013, Vol. 9, No. 1 , Pages 1-162||陶斐（UTD） |- ASR和WFST|| |- Biing-Hwang Juang, Wu Chou, Member, and Chin-Hui Lee，Minimum classification |- error rate methods for speech recognition||洪青阳（厦门大学） |- 区分性训练MCE|| |- |Daniel Povey.Discriminative Training for Large Vocabulary Speech Recognition. |- 杨嵩（驰声科技）||声学模型区分性训练|| |- |Has¸im Sak, Andrew Senior, Kanishka Rao, Franc¸oise Beaufays, Fast and |- Accurate Recurrent Neural Network Acoustic Models for Speech Recognition |- 徐海华（南阳理工大学），苏牧（云知声）||CTC |- |Alex Graves, Supervised Sequence Labeling with Recurrent Neural Networks. Phd |- thesis.||汤本来（南开），李博（谷歌）||LSTM，CTC|| |- |Fast and Accurate Recurrent Neural Network Acoustic Models for Speech |- Recognition.Has¸im Sak, Andrew Senior, Kanishka Rao, Franc¸oise Beaufays |- 徐海华（南洋理工大学）||CTC||http://arxiv.org/pdf/1507.06947.pdf |- |Lattice-based optimization of sequence classification criteria for |- neural-network acoustic modeling by Brian Kingsbury, IBM Watson |- 王广森（新加坡I2R）|||| |- |MJF Gales:Maximum likelihood linear transformations for HMM-based speech |- recognition.《Computer Speech & Language》, 1998, 12(2):75–98 |- 钱彦旻（上海交大）||MLLR|| |- |Woodland, P.C.: Maximum likelihood linear regression for speaker adaptation of |- continuous density hidden Markov models. Computer Speech and Language 9(2), |- 171-185||钱彦旻（上海交大）||MLLR|| |- |Tandem connectionist feature extraction for conventional HMM |- systems，hermansky||钱彦旻（上海交大）||自适应|| |- Subspace Gaussian mixture models for speech recognition. Povey, D. |- 钱彦旻（上海交大）||dan的SGMM|| |- |A novel scheme for speaker recognition using a phonetically-aware deep neural |- network Y Lei, N Scheffer, L Ferrer, M McLaren ||夏瑞（Intel Lab）|||| |- |Campbell W M, Sturim D E, Reynolds D A. Support vector machines using GMM |- supervectors for speaker verification[J]. Signal Processing Letters, IEEE, |- 2006, 13(5): 308-311. ||龙艳花（上海师范大学）||基于SVM声纹识别方面的文章|| |- |Campbell W M, Sturim D E, Reynolds D A, et al. SVM based speaker verification |- using a GMM supervector kernel and NAP variability compensation[C]//Acoustics, |- Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE |- |- International Conference on. IEEE, 2006, 1: I-I. ||龙艳花（上海师范大学） |- 基于SVM声纹识别方面的文章|| |- |Douglas A. Reynolds, Thomas F. Quatieri, and Robert B. Dunn, Speaker |- Verfication Using Adapted Gaussian Mixture Models||洪青阳（厦门大学） |- 说话人识别，GMM-UBM|| |- |Najim Dehak, Patrick Kenny, R′eda Dehak, Pierre Dumouchel, and Pierre Ouellet, |- Front-End Factor Analysis For Speaker Verification||洪青阳（厦门大学） |- 说话人识别，i-vector|| |- |Analysis of I-vector Length Normalization in Speaker Recognition Systems |- Daniel Garcia-Romero and Carol Y. Espy-Wilson||许敏强（阿里巴巴）||length |- normalization + PLDA|| |- |Within-Class Covariance Normalization for SVM-based Speaker Recognition Andrew |- O. Hatch, Sachin Kajarekar, and Andreas Stolcke||许敏强（阿里巴巴） |- speaker方向,这个论文的方法，不仅可以用于speaker，还可以推广到图像识别、分类等领域，效果明显|| |- |Silke M Witt, Steve J Young, Phone-level pronunciation scoring and assessment |- for interactive language learning, 2000, Speech Communication |- 黄浩（新疆大学）||GOP以及错误检测|| |- |S. M. Witt.Use of Speech Recognition in Computer-assisted Language learning |- 杨嵩（驰声科技）||语音评测|| |- |Andrew J. Hunt, Alan W. Black, Unit selection in a concatenative speech |- synthesis system using a large speech database, ICASSP1996.||康永国（百度） |- 拼接语音合成的典型工作|| |- |Zen H, Tokuda K, Black A W. Statistical parametric speech synthesis[J]. Speech |- Communication, 2009, 51(11): 1039-1064.||凌振华（中科大） |- HMM统计参数语音合成|| |- |Tokuda K, Nankaku Y, Toda T, et al. Speech synthesis based on hidden Markov |- models[J]. Proceedings of the IEEE, 2013, 101(5): 1234-1252. |- 凌振华（中科大）||HMM统计参数语音合成|| |- |Zee, H., Senior, A., Schuster. M. 2013, Statistical parametric speech sythesis |- |- using deep neural networks||吴君如（华东师大），康永国（百度）|||| |- K. Tokuda, T. Yoshimura, T. Masuko, T. Kobayashi, T. Kitamura, Speech |- |parameter generation algorithms for HMM-based speech synthesis, Proc. of |- ICASSP, pp.1315-1318, June 2000||康永国（百度）||HMM统计参数语音合成|| |- S. King, "A reading list of recent advances in speech synthesis", Proc. ICPhS |- 2015.||武执正（爱丁堡大学），杨鹏（百度） |- https://www.internationalphoneticassociation.org/icphs-proceedings/ICPhS2015/Papers/ICPHS1043.pdf |- |statistical parametric speech synthesis，Heiga Zen||杨辰雨（新加坡I2R） |- 语音合成声学建模方面|| |- |ZH Ling:Deep Learning for Acoustic Modeling in Parametric Speech |- Generation.《Signal Processing Magazine IEEE》, 2015, 32(3):35-52 |- 杨辰雨（新加坡I2R）||语音合成声学建模方面|| |- |Xu Yi. Separation of functional components of tone and intonation from |- observed F0 patterns.||林怡亭（Nuance）,李雅（中科院自动化所）|||| |- Shriberg, E., Stolcke, A., Hakkani-Tür, D., & Tür, G. (2000). Prosody-based |- |automatic segmentation of speech into sentences and topics. Speech |- communication, 32(1), 127-154.||陈磊（ETS语音评测），谢磊（西工大） |- SRI使用Prosody信息做语音结构化切分的工作，Google Scholar 引用 430|| |- |ToBI: A standard for labeling English prosody||杨辰雨（新加坡I2R） |- 中英文韵律标注|| |- |chinese prosody and prosodic labeling of spontaneous speech |- 杨辰雨（新加坡I2R）||C-ToBI 3.0|| |- |Shrikanth S. Narayanan and Panayiotis Georgiou, Behavioral Signal Processing: |- Deriving Human Behavioral Informatics from Speech and Language (2013), in: |- Proceedings of IEEE, 101:5(1203 - 1233) ||李明（中山大学） |- 语音及多模态行为信号分析的综述性paper 推荐给做情感计算和行为分析这一领域的人|| |- |Levelt. W, Roelofs. A, 1999, A theory of lexical access in speech production. |- 吴君如（华东师大） |- 语言认知领域，本文为心理语言学界到90年代末为止，对人类语言产生心理过程实证研究结果及机制探讨最全面的总结，不少计算模型都以重现本文列举的效应为目标 |- |- |A Highly Robust Audio Fingerprinting System，Pilips 的Jaap Haitsma |- 朱磊（芋头科技）||audio fingerprint|| |- |Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality. In Proceedings of NIPS, 2013. |- 陈谐(剑桥）|||| |- |Dzmitry Bahdanau, KyungHyun Cho, Yoshua Bengio, Neural Machine Translation By |- Jointly Learning To Align And Translate |- 肖雄（南洋理工大学）,徐海华（南洋理工大学）||attention model for MT |- http://arxiv.org/pdf/1409.0473.pdf |- || |- |||||| |- Book and Thesis|||||| |- |《Spoken Language Processing: A Guide to Theory, Algorithm, and System |- Development》 黄学东||何伟（中国传媒大学）钱彦旻（上海交大）|||| |- |自然语言处理综论，daniel jurafsky||汪淼淼（阿里巴巴）|||| |- |Speech enhancement theory and practice, Philipos C. Loizou, |- 张学良（内蒙古大学）||语音增强的书|| |- |Statistical methods for speech recognition, Jenilek，||金琴（中国人民大学） |- 经典教材|| |- |Hidden Markov Models for Speech Recognition (Edinburgh University Press 1990) |- 穆向禹（百度）|||| |- |Machine Learning Paradigms for Speech Recognition||卢鲤（腾讯） |- 用机器学习的观点看语音识别，框架非常清晰|| |- 《实用语音识别基础》，国防工业出版社||王晶（北理工）|||| |- |Text-to-speech synthesis, Paul Taylor, University of Cambridge |- 黄东延（新加坡）||||书对text-to-speech 怎样work 给了详细深入的解释 |- |A course in phonetics, Ladefoged||冯卉（天津大学）||群内多人推荐|| |- |A Course in Phonetics (7th Ed.). P. Ladeforged & K. Johnson (2015). Cengage |- Learning. ||顾文涛（南京师范大学）||很好的入门级教科书|| |- |Acoustics and Auditory Phonetics (3rd Ed.).K. Johnson (2012). |- |- Wiley-Blackwell.||顾文涛（南京师范大学）|||| |- |Articulatory Phonetics. B. Gick, I. Wilson, & D. Derrick (2013). |- Wiley-Blackwell.||顾文涛（南京师范大学）|||| |- |实验语音学概要，实验语音学概要 修订版||熊子瑜（语言所），时秀娟（天津师大）|||| |- |实验语音学基础教程，孔江平||时秀娟（天津师大）|||| |- |Phonetics，Reetz & Jongman||孙锐欣（华东师大） |- 国内李爱军老师等在翻译中文版|| |- |《实验语音学概要》吴宗济||王磊（音乐雷达）等||语音合成--音韵学|| |- |自然语言处理综论，Daniel Jurafsky|||||| |- |Duda的Pattern Classification 第二版，有中文版||谢凌云（中国传媒大学） |- 模式识别|| |- |《现代汉语音典》蔡莲红、孔江平||王愈（捷通华声）|||| |- |《汉语语调实验研究》2012年，作者林茂灿||李爱军（社科院语言所） |- |在英语语调理论AM基础上对汉语语调的研究|| |- |Sun-Ah Jun写的prosodic |- topology，中科院声学所吕士楠老师将之翻译为中文版《韵律类型学》 |- 郝玉峰（海天瑞声）||多语言韵律标注|| |- |Kenneth N. Stevens的Acoustic Phonetics||解炎陆（北京语言大学） |- 从acoustic的角度阐述了各种发音的特征，原版太贵，希望国内能出版。|| |- |"Ladefoged《世界语音》 |- "||时秀娟（天津师大） |- http://mp.weixin.qq.com/s?__biz=MzA3OTI3MjEzNg==&mid=400341406&idx=2&sn=484d61f4ab9dcfe7bb613bb8d119a161&scene=1&srcid=1104uQiKdYcy75BYTBJ9xA99#rd |- |Theory and Applications of Digital Speech Processing, Lawrence Rabiner， |- 党建武（天津大学）|||| |- |T. F. Quatieri, Discrete-time speech signal processing（英文版） |- 王晶（北理工）||经典的语音信号处理课程教材|| |- |《信号与系统》奥本海《Signals and Systems》Alan V. Oppenheim||陈谐(剑桥）|||| |- |Microphone Arrays: Signal Processing Techniques and Applications (Digital |- |Signal Processing) by Michael Brandstein, Darren Ward, Springer, 2001. |- |- 李军锋（中科院声学所）||语音信号处理领域|| |- |Pattern recognition and meachine learning||王东（清华） |- 机器学习领域经典大作|| |- |Machine learning a probabilistic perspective，machine learning algorithmic |- perspective||卢鲤（腾讯）|||| |- |Introduction to statistical pattern recognition. Keinosuke Fukunaga |- 朱璇（三星北京研究院）||模式识别 |- 这本书对于特征空间的表述非常清晰，深入浅出，很适合初学者。 |- |An introduction for support vector machine||朱璇（三星北京研究院）||svm|| |- |步尚全《基础泛函分析》||邓侃(思昂教育）||泛函|| |- |<<测度论与概率论基础>>，北京大学出版社||明怀平（新加坡I2R） |- 我推荐一个数学基础的，|| |- |Daniel Povey, "Discriminative Training for Large Vocabulary Speech |- Recognition," PhD thesis, Cambridge University Engineering Dept, 2003 |- 俞凯（上海交大）||鉴别性训练，博士论文|| |- |语境相关的声学模型和搜索策略的研究，高升，中国科学院博士论文，2001 |- 李宏言（阿里巴巴）||国内早期lvcsr的力作|| |- |||||| |- |Tools|||||| |- |HTK book|||||| |- |Kaldi|||||| |- |Praat|||||| |- |Theano|||||| |- |CNTK|||||| |- |RNNLIB|||||| |- |Eesen ||||CTC toolkit||https://github.com/yajiemiao/eesen |- |||||| |- |Video & online course|||||| |- |Deep Learning Summer School, Montreal 2015 |- |- http://videolectures.net/deeplearning2015_montreal/ |- |INTRODUCTION TO DIGITAL FILTERS ||王愈（捷通华声） |- |一套在线的信号处理教程,深入浅出地讲解了信号分析处理的基础知识，并结合Matlab常用的信号系统库函数——如freqz——推导讲解简明透彻。 |- https://ccrma.stanford.edu/~jos/filters/ |- |九州语言网||李爱军（社科院语言所） |- |对汉语方言语法、语音感兴趣的，可以访问熊子瑜负责的语言所在建九州语言网 |- http://9zhou.phonetics.org.cn/ |-