Robust numeric recognition in spoken language dialogue

被引:7
|
作者
Rahim, M [1 ]
Riccardi, G [1 ]
Saul, L [1 ]
Wright, J [1 ]
Buntschuh, B [1 ]
Gorin, A [1 ]
机构
[1] AT&T Labs Res, Florham Pk, NJ 07932 USA
关键词
robustness; spoken dialogue system; speech recognition; utterance verification; discriminative training; understanding; language modeling; numeric recognition; digits;
D O I
10.1016/S0167-6393(00)00054-6
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
This paper addresses the problem of automatic numeric recognition and understanding in spoken language dialogue. We show that accurate numeric understanding in fluent unconstrained speech demands maintaining robustness at several different levels of system design, including acoustic, language, understanding and dialogue. We describe a robust system for numeric recognition and present algorithms for feature extraction, acoustic and language modeling, discriminative training, utterance verification and numeric understanding and validation. Experimental results from a field-trial of a spoken dialogue system are presented that include customers' responses to credit card and telephone number requests. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:195 / 212
页数:18
相关论文
共 50 条
  • [21] Deep Contextual Language Understanding in Spoken Dialogue Systems
    Liu, Chunxi
    Xu, Puyang
    Sarikaya, Ruhi
    16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5, 2015, : 120 - 124
  • [22] The role of spoken language dialogue interaction in intelligent environments
    Minker, Wolfgang
    Lopez-Cozar, Ramon
    McTear, Michael
    JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS, 2009, 1 (01) : 31 - 36
  • [23] Automatic Spoken Language Acquisition Based on Observation and Dialogue
    Komatsu, Ryota
    Gao, Shengzhou
    Hou, Wenxin
    Zhang, Mingxin
    Tanaka, Tomohiro
    Toyoda, Keisuke
    Kimura, Yusuke
    Hino, Kent
    Iwamoto, Yu
    Mori, Kosuke
    Okamoto, Takuma
    Shinozaki, Takahiro
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2022, 16 (06) : 1480 - 1492
  • [24] Endowing spoken language dialogue systems with emotional intelligence
    André, E
    Rehm, M
    Minker, W
    Bühler, D
    AFFECTIVE DIALOGUE SYSTEMS, PROCEEDINGS, 2004, 3068 : 178 - 187
  • [25] Improvement of the recognition rate of spoken queries to the dialogue system
    Matousek, V
    Ocelíková, J
    TEXT, SPEECH AND DIALOGUE, 1999, 1692 : 308 - 314
  • [26] A Spoken Language Interpretation Component for a Robot Dialogue System
    Makalic, Enes
    Zukerman, Ingrid
    Niemann, Michael
    INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5, 2008, : 195 - 198
  • [27] YEAH RIGHT: SARCASM RECOGNITION FOR SPOKEN DIALOGUE SYSTEMS
    Tepperman, Joseph
    Traum, David
    Narayanan, Shrikanth
    INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, VOLS 1-5, 2006, : 1838 - +
  • [28] SPONTANEOUS SPEECH RECOGNITION FOR ROMANIAN IN SPOKEN DIALOGUE SYSTEMS
    Burileanu, Corneliu
    Popescu, Vladimir
    Buzo, Andi
    Petrea, Cristina Sorina
    Ghelmez-Hanes, Diana
    PROCEEDINGS OF THE ROMANIAN ACADEMY SERIES A-MATHEMATICS PHYSICS TECHNICAL SCIENCES INFORMATION SCIENCE, 2010, 11 (01): : 83 - 91
  • [29] Spoken Language Recognition With Prosodic Features
    Ng, Raymond W. M.
    Lee, Tan
    Leung, Cheung-Chi
    Ma, Bin
    Li, Haizhou
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2013, 21 (09): : 1841 - 1853
  • [30] Spoken language recognition with relevance feedback
    Tong, Rong
    Li, Haizhou
    Ma, Bin
    Chng, Eng Siong
    Cho, Siu-Yeung
    2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL IV, PTS 1-3, 2007, : 861 - +