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A long-contextual-span model of resonance dynamics for speech recognition: Parameter learning and recognizer evaluation

机译：用于语音识别的共振动力学的长上下文跨度模型：参数学习和识别器评估

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Li Deng; Dong Yu; Xiaolong Li; Alex Acero;
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年度 2005
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1. Spontaneous speech recognition using a statistical coarticulatory model for the vocal-tract-resonance dynamics [J] . Li Deng, Jeff Ma The Journal of the Acoustical Society of America . 2000,第6期

机译：使用统计共发音模型的自发语音识别，用于声道共振动态
2. Bayesian adaptive learning of the parameters of hidden Markov model for speech recognition [J] . Qiang Huo, Chorkin Chan IEEE Transactions on Speech and Audio Proceeding . 1995,第5期

机译：语音识别的隐马尔可夫模型参数的贝叶斯自适应学习
3. Bayesian adaptive learning of the parameters of hidden Markov modelfor speech recognition [J] . Qiang Huo, Chorkin Chan, Chin Hui Lee IEEE Transactions on Speech and Audio Proceessing . 1995,第5期

机译：语音识别的隐马尔可夫模型参数的贝叶斯自适应学习
4. A Long-Contextual-Span Model of Resonance Dynamics for Speech Recognition: Parameter Learning and Recognizer Evaluation [C] . Li Deng, Dong Yu, Xiaolong Li, . 2005

机译：用于语音识别的共振动力学的长上下文跨度模型：参数学习和识别器评估
5. Speaker dynamics as a source of pronunciation variability for continuous speech recognition models. [D] . Bates, Rebecca Anne. 2004

机译：说话人动态是连续语音识别模型的发音可变性来源。
6. Using semi-quantitative dynamic contrast-enhanced magnetic resonance imaging parameters to evaluate tumor hypoxia: a preclinical feasibility study in a maxillofacial VX2 rabbit model [O] . Linfeng Zheng, Yujie Li, Feng Geng, 2015

机译：使用半定量动态对比增强磁共振成像参数评估肿瘤缺氧：颌面部VX2兔模型的临床前可行性研究
7. Bayesian adaptive learning of the parameters of hidden Markov model for speech recognition [O] . Huo Q, Chan C, Lee CH 1995

机译：用于语音识别的隐马尔可夫模型参数的贝叶斯自适应学习
8. Leveraging Multimodal Redundancy for Dynamic Learning, with SHACER - a Speech and HAndwriting reCognizER. [R] . E. C. Kaiser 2007

机译：利用多模式冗余进行动态学习，使用sHaCER - 语音和编辑重新识别。

A long-contextual-span model of resonance dynamics for speech recognition: Parameter learning and recognizer evaluation

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