Lexical Stress Modeling for Improved Speech Recognition of Spontaneous Telephone Speech in the JUPITER Domain

机译：JUPITER域中用于增强自发电话语音识别的词汇应力模型

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This paper examines an approach of using lexical stress models to improve the speech recognition performance on spontaneous telephone speech. We analyzed the correlation of various pitch, energy, and duration measurements with lexical stress on a large corpus of spontaneous utterances, and identified the most informative features of stress using classification experiments. We incorporated the stress models into the recognizer first-pass Viterbi search and obtained modest but statistically significant improvements over a state-of-the-art real-time performance on the JUPITER weather information domain.

机译：本文研究了一种使用词法重音模型来提高自发电话语音的语音识别性能的方法。我们分析了各种音调，能量和持续时间测量值与大自然发声体上的词汇应力的相关性，并使用分类实验确定了应力最大的信息特征。我们将压力模型整合到识别器的首遍维特比搜索中，并获得了JUPITER天气信息领域最新动态性能的适度但统计上显着的改进。

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《European Conference on Speech Communication and Technology v.4; 20010903-20010907; Aalborg; DK》|2001年|P.2761-2764|共4页
会议地点 Aalborg(DK);Aalborg(DK)
作者
Chao Wang; Stephanie Seneff;
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Spoken Language Systems Group MIT Laboratory for Computer Science Cambridge, Massachusetts 02139, USA;

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正文语种 eng
中图分类传播理论;
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专利

1. HMM-based stressed speech modeling with application to improved synthesis and recognition of isolated speech under stress [J] . Bou-Ghazale S.E., Hansen J.H.L. IEEE Transactions on Speech and Audio Proceeding . 1998,第3期

机译：基于HMM的压力语音建模及其在压力下孤立语音的合成和识别中的应用
2. Modeling lexical stress in continuous speech recognition for Dutch [J] . Henk van den Heuvel, David van Kuijk, Lou Boves Speech Communication . 2003,第3期

机译：在荷兰语的连续语音识别中建模词汇重音
3. HMM-based stressed speech modeling with application to improvedsynthesis and recognition of isolated speech under stress [J] . Bou-Ghazale S.E., Hansen J.H.L. IEEE Transactions on Speech and Audio Proceessing . 1998,第3期

机译：基于HMM的压力语音建模及其在压力下孤立语音的合成和识别中的应用
4. Lexical Stress Modeling for Improved Speech Recognition of Spontaneous Telephone Speech in the JUPITER Domain [C] . Chao Wang, Stephanie Seneff European conference on speech communication and technology . 2001

机译：改进木星域自发电话语音语音识别的词汇应力建模
5. Learning local lexical structure in spontaneous speech language modeling [D] . Siu, Man-Hung 1998

机译：在自发语音语言建模中学习局部词汇结构
6. Low-frequency fine-structure cues allow for the online use of lexical stress during spoken-word recognition in spectrally degraded speech [O] . Ying-Yee Kong, Alexandra Jesse -1

机译：低频精细结构提示可在频谱退化语音中的口语识别过程中在线使用词法重音
7. Real-Time Telephone-Based Speech Recognition In The Jupiter Domain [O] . James R. Glass, Timothy J. Hazen, I. Lee Hetherington 1999

机译：木星域中基于实时电话的语音识别
8. Improving on hidden Markov models: An articulatorily constrained, maximum likelihood approach to speech recognition and speech coding [R] . Hogden, J. 1996

机译：改进隐马尔可夫模型：语音识别和语音编码的语义约束，最大似然方法

Lexical Stress Modeling for Improved Speech Recognition of Spontaneous Telephone Speech in the JUPITER Domain

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