Article

A phonotactic-semantic paradigm for automatic spoken document classification

Authors:

Haizhou LiAuthors Info & Claims

SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 369 - 376

https://doi.org/10.1145/1076034.1076098

Published: 15 August 2005 Publication History

Abstract

We demonstrate a phonotactic-semantic paradigm for spoken document categorization. In this framework, we define a set of acoustic words instead of lexical words to represent acoustic activities in spoken languages. The strategy for acoustic vocabulary selection is studied by comparing different feature selection methods. With an appropriate acoustic vocabulary, a voice tokenizer converts a spoken document into a text-like document of acoustic words. Thus, a spoken document can be represented by a count vector, named a bag-of-sounds vector, which characterizes a spoken document's semantic domain. We study two phonotactic-semantic classifiers, the support vector machine classifier and the latent semantic analysis classifier, and their properties. The phonotactic-semantic framework constitutes a new paradigm in spoken document classification, as demonstrated by its success in the spoken language identification task. It achieves 18.2% error reduction over state-of-the-art benchmark performance on the 1996 NIST Language Recognition Evaluation database.

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Cited By

Tejedor JToledano DLopez-Otero PDocio-Fernandez LSerrano LHernaez ICoucheiro-Limeres AFerreiros JOlcoz JLlombart J(2017)ALBAYZIN 2016 spoken term detection evaluationEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-017-0119-z2017:1(1-23)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1186/s13636-017-0119-z
Wang DKing SFrankel JVipperla REvans NTroncy R(2012)Direct posterior confidence for out-of-vocabulary spoken term detectionACM Transactions on Information Systems10.1145/2328967.232896930:3(1-34)Online publication date: 6-Sep-2012
https://dl.acm.org/doi/10.1145/2328967.2328969
Wang DTejedor JKing SFrankel J(2012)Term-Dependent Confidence Normalisation for Out-of-Vocabulary Spoken Term DetectionJournal of Computer Science and Technology10.1007/s11390-012-1228-x27:2(358-375)Online publication date: 5-Mar-2012
https://doi.org/10.1007/s11390-012-1228-x
Show More Cited By

Index Terms

A phonotactic-semantic paradigm for automatic spoken document classification
1. Applied computing
  1. Arts and humanities
    1. Sound and music computing
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees

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Published In

cover image ACM Conferences

SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval

August 2005

708 pages

ISBN:1595930345

DOI:10.1145/1076034

General Chairs:
Ricardo Baeza-Yates
University of Chile, Chile
,
Nivio Ziviani
Federal University of Minas Gerais, Brazil
,
Program Chairs:
Gary Marchionini
University of North Carolina, USA
,
Alistair Moffat
University of Melbourne, Australia
,
John Tait
University of Sunderland, UK

Copyright © 2005 ACM.

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Published: 15 August 2005

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SIGIR05: The 28th ACM/SIGIR International Symposium on Information Retrieval 2005

August 15 - 19, 2005

Salvador, Brazil

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Tejedor JToledano DLopez-Otero PDocio-Fernandez LSerrano LHernaez ICoucheiro-Limeres AFerreiros JOlcoz JLlombart J(2017)ALBAYZIN 2016 spoken term detection evaluationEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-017-0119-z2017:1(1-23)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1186/s13636-017-0119-z
Wang DKing SFrankel JVipperla REvans NTroncy R(2012)Direct posterior confidence for out-of-vocabulary spoken term detectionACM Transactions on Information Systems10.1145/2328967.232896930:3(1-34)Online publication date: 6-Sep-2012
https://dl.acm.org/doi/10.1145/2328967.2328969
Wang DTejedor JKing SFrankel J(2012)Term-Dependent Confidence Normalisation for Out-of-Vocabulary Spoken Term DetectionJournal of Computer Science and Technology10.1007/s11390-012-1228-x27:2(358-375)Online publication date: 5-Mar-2012
https://doi.org/10.1007/s11390-012-1228-x
Biatov KKoehler JSchneider D(2009)Audio Clips Content Comparison Using Latent Semantic IndexingProceedings of the 2009 IEEE International Conference on Semantic Computing10.1109/ICSC.2009.21(509-512)Online publication date: 14-Sep-2009
https://dl.acm.org/doi/10.1109/ICSC.2009.21
Richardson FCampbell W(2008)Language recognition with discriminative keyword selection2008 IEEE International Conference on Acoustics, Speech and Signal Processing10.1109/ICASSP.2008.4518567(4145-4148)Online publication date: Mar-2008
https://doi.org/10.1109/ICASSP.2008.4518567
Yi-cheng Pan Lin-shan Lee (2007)Type-II dialogue systems for information access from unstructured knowledge sources2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)10.1109/ASRU.2007.4430170(544-549)Online publication date: Dec-2007
https://doi.org/10.1109/ASRU.2007.4430170
Maddage NLi HKankanhalli MEfthimiadis EDumais SHawking DJärvelin, K(2006)Music structure based vector space retrievalProceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval10.1145/1148170.1148185(67-74)Online publication date: 6-Aug-2006
https://dl.acm.org/doi/10.1145/1148170.1148185
Rong Tong Bin Ma Donglai Zhu Haizhou Li Eng Siong Chng (2006)Integrating Acoustic, Prosodic and Phonotactic Features for Spoken Language Identification2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings10.1109/ICASSP.2006.1659993(I-205-I-208)Online publication date: 2006
https://doi.org/10.1109/ICASSP.2006.1659993

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