IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.最新文献_第6页

Recognition experiments with the SpeechDat-Car Aurora Spanish database using 8 kHz- and 16 kHz-sampled signals 使用8千赫和16千赫采样信号的speech - dat - car Aurora西班牙数据库进行识别实验

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034606

C. Nadeu, M. Tolos

引用次数: 3

Collaborative steering of microphone array and video camera toward multi-lingual tele-conference through speech-to-speech translation 通过语音到语音的翻译，将麦克风阵列和摄像机协同导向多语种电话会议

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034602

T. Nishiura, R. Gruhn, S. Nakamura

引用次数: 7

Transducer composition for "on-the-fly" lexicon and language model integration 用于“即时”词汇和语言模型集成的换能器组成

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034667

D. Caseiro, I. Trancoso

引用次数: 28

Searching for the missing piece [speech recognition] 寻找丢失的碎片[语音识别]

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034629

W. N. Choi, Y. W. Wong, T. Lee, P. Ching

引用次数: 0

Simultaneous recognition of distant talking speech of multiple sound sources based on 3-D N-best search algorithm 基于三维n -最优搜索算法的远距离多声源语音同时识别

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034600

P. Heracleous, S. Nakamura, K. Shikano

引用次数: 1

Acoustic analysis and recognition of whispered speech 低声语音的声学分析与识别

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034676

Taisuke Itoh, K. Takeda, F. Itakura

引用次数: 13

Robust speaker clustering in eigenspace 特征空间中的鲁棒说话人聚类

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034588

R. Faltlhauser, G. Ruske

{"title":"Robust speaker clustering in eigenspace","authors":"R. Faltlhauser, G. Ruske","doi":"10.1109/ASRU.2001.1034588","DOIUrl":"https://doi.org/10.1109/ASRU.2001.1034588","url":null,"abstract":"We propose a speaker clustering scheme working in 'eigenspace'. Speaker models are transformed to a low-dimensional subspace using 'eigenvoices'. For the speaker clustering procedure, simple distance measures, e.g. Euclidean distance, can be applied. Moreover, clustering can be accomplished with base models (for eigenvoice projection) like Gaussian mixture models as well as conventional HMMs. In case of HMMs, re-projection to the original space readily yields acoustic models. Clustering in subspace produces a well-balanced cluster and is easy to control. In the field of speaker adaptation, several principal techniques can be distinguished. The most prominent among them are Bayesian adaptation (e.g. MAP), transformation based approaches (MLLR - maximum likelihood linear regression), as well as so-called eigenspace techniques. Especially the latter have become increasingly popular, as they make use of a-priori information about the distribution of speaker models. The basic approach is commonly called the eigenvoice (EV) approach. Besides these techniques, speaker clustering is a further attractive adaptation scheme, especially since it can be - and has been - easily combined with the above methods.","PeriodicalId":118671,"journal":{"name":"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131693597","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: 25

Evaluating dialogue strategies and user behavior 评估对话策略和用户行为

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034630

M. Danieli

{"title":"Evaluating dialogue strategies and user behavior","authors":"M. Danieli","doi":"10.1109/ASRU.2001.1034630","DOIUrl":"https://doi.org/10.1109/ASRU.2001.1034630","url":null,"abstract":"Summary form only given. The need for accurate and flexible evaluation frameworks for spoken and multimodal dialogue systems has become crucial. In the early design phases of spoken dialogue systems, it is worthwhile evaluating the user's easiness in interacting with different dialogue strategies, rather than the efficiency of the dialogue system in providing the required information. The success of a task-oriented dialogue system greatly depends on the ability of providing a meaningful match between user's expectations and system capabilities, and a good trade-off improves the user's effectiveness. The evaluation methodology requires three steps. The first step has the goal of individuating the different tokens and relations that constitute the user mental model of the task. Once tokens and relations are considered for designing one or more dialogue strategies, the evaluation enters its second step which is constituted by a between-group experiment. Each strategy is tried by a representative set of experimental subjects. The third step includes measuring user effectiveness in providing the spoken dialogue system with the information it needs to solve the task. The paper argues that the application of the three-steps evaluation method may increase our understanding of the user mental model of a task during early stages of development of a spoken language agent. Experimental data supporting this claim are reported.","PeriodicalId":118671,"journal":{"name":"IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.","volume":"474 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131835448","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

Incremental language models for speech recognition using finite-state transducers 使用有限状态换能器的语音识别增量语言模型

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034620

Hans J. G. A. Dolfing, I. L. Hetherington

引用次数: 50

Speech interfaces for mobile communications 用于移动通信的语音接口

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. Pub Date : 2001-12-09 DOI: 10.1109/ASRU.2001.1034596

H. Nakano

引用次数: 2