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2008 6th International Symposium on Chinese Spoken Language Processing最新文献

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Improving HMM Based Speech Synthesis by Reducing Over-Smoothing Problems 通过减少过度平滑问题改进HMM语音合成
2008 6th International Symposium on Chinese Spoken Language Processing Pub Date : 2008-12-01 DOI: 10.1109/CHINSL.2008.ECP.16
Meng Zhang, J. Tao, Huibin Jia, Xia Wang
{"title":"Improving HMM Based Speech Synthesis by Reducing Over-Smoothing Problems","authors":"Meng Zhang, J. Tao, Huibin Jia, Xia Wang","doi":"10.1109/CHINSL.2008.ECP.16","DOIUrl":"https://doi.org/10.1109/CHINSL.2008.ECP.16","url":null,"abstract":"Although hidden Markov model based speech synthesis has been proved to have good performance, there are still some factors which degrade the quality of synthesized speech: vocoder, model accuracy and over-smoothing. This paper analyzes these factors separately. Modifications for removing different factors are proposed. Experimental results show that over-smoothing in frequency domain mainly affect the quality of synthesized speech whereas over-smoothing in time domain can nearly be ignored. Time domain over-smoothing is generally caused by model structure accuracy problem and frequency domain over- smoothing is caused by training algorithm accuracy problem. Currently used model structure is capable of representing speech without quality degradation. ML-estimation based parameter training algorithm causes distortion of perception in speech synthesis. Modification for improving parameter training algorithm is more likely to improve the synthesizing performance.","PeriodicalId":291958,"journal":{"name":"2008 6th International Symposium on Chinese Spoken Language Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114749086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Effect of Feature Smoothing for Robust Speech Recognition 特征平滑对鲁棒语音识别的影响
2008 6th International Symposium on Chinese Spoken Language Processing Pub Date : 2008-12-01 DOI: 10.1109/CHINSL.2008.ECP.30
Xiong Xiao, Chng Eng Siong, Haizhou Li
{"title":"Effect of Feature Smoothing for Robust Speech Recognition","authors":"Xiong Xiao, Chng Eng Siong, Haizhou Li","doi":"10.1109/CHINSL.2008.ECP.30","DOIUrl":"https://doi.org/10.1109/CHINSL.2008.ECP.30","url":null,"abstract":"One class of feature enhancement techniques improve features robustness by performing temporal filtering to smooth the feature trajectories. While smoothing can enhance the features robustness by reducing the intra-class variation of the features, it also compromises the features discriminative power by reducing their inter-class distance. In this paper, we investigate the effect of feature smoothing on speech recognition performance. To evaluate how different degrees of smoothing will affect the performance, the speech features are low-pass filtered with different cut-off frequencies and then used for model training and recognition. From the experimental results, we have two observations: 1) the noisy speech needs more aggressive feature smoothing; 2) the large vocabulary Aurora-4 task prefers less smoothing than the small vocabulary Aurora-2 task.","PeriodicalId":291958,"journal":{"name":"2008 6th International Symposium on Chinese Spoken Language Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123745294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting Spectral and Prosodic Parameters for Unit Selection in Speech Synthesis 预测语音合成中单位选择的频谱和韵律参数
2008 6th International Symposium on Chinese Spoken Language Processing Pub Date : 2008-12-01 DOI: 10.1109/CHINSL.2008.ECP.45
M. Dong, Haizhou Li
{"title":"Predicting Spectral and Prosodic Parameters for Unit Selection in Speech Synthesis","authors":"M. Dong, Haizhou Li","doi":"10.1109/CHINSL.2008.ECP.45","DOIUrl":"https://doi.org/10.1109/CHINSL.2008.ECP.45","url":null,"abstract":"We usually build a prosody model to predict the prosodic parameters, which will be used as part of the criteria for unit selection. Spectral appropriateness of units is usually ensured by using identities of context units, which are linguistic symbols. With looking into the spectral properties of the actual signal, the spectral mismatches are often perceived in the synthetic speech. In this paper, we propose to use MFCC as spectral parameters in addition to the prosodic parameters. By introducing the spectral parameters into the criteria for unit selection, the appropriateness of units can determined by statistical models. Thus the possibility of abnormal spectral mismatches between the concatenated units can be reduced. Experiments show that the approach helps to improve the quality of synthetic speech.","PeriodicalId":291958,"journal":{"name":"2008 6th International Symposium on Chinese Spoken Language Processing","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125743206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Trellis Based Fast Lattice Generating Algorithm 一种基于网格的快速格生成算法
2008 6th International Symposium on Chinese Spoken Language Processing Pub Date : 2008-12-01 DOI: 10.1109/CHINSL.2008.ECP.59
Wei Li, Ji Wu, Zhiguo Wang
{"title":"A Trellis Based Fast Lattice Generating Algorithm","authors":"Wei Li, Ji Wu, Zhiguo Wang","doi":"10.1109/CHINSL.2008.ECP.59","DOIUrl":"https://doi.org/10.1109/CHINSL.2008.ECP.59","url":null,"abstract":"Lattice is widely used as a kind of the search results in Large Vocabulary Continuous Speech Recognition (LVCSR). A new lattice-generation algorithm is presented in this paper. The algorithm is based on a classical forward-backward decoding method, which is proved to be highly efficient. Moreover, some improvements have been done to satisfy the requirements in the lattice decoding. Two Chinese mandarin large-scale speech recognition tasks are used to evaluate the proposed algorithm and the experimental results show that our algorithm can both improve decoding speed and save decoding space significantly without sacrificing the recognition accuracy, compared with the widely used Lattice decoding method as.","PeriodicalId":291958,"journal":{"name":"2008 6th International Symposium on Chinese Spoken Language Processing","volume":"34 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125239768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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