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Multi-scale personalization for voice search applications

Authors:

Daniel Bolaños,

Geoffrey Zweig,

Patrick NguyenAuthors Info & Claims

NAACL-Short '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

Pages 101 - 104

Published: 31 May 2009 Publication History

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Abstract

Voice Search applications provide a very convenient and direct access to a broad variety of services and information. However, due to the vast amount of information available and the open nature of the spoken queries, these applications still suffer from recognition errors. This paper explores the utilization of personalization features for the post-processing of recognition results in the form of n-best lists. Personalization is carried out from three different angles: short-term, long-term and Web-based, and a large variety of features are proposed for use in a log-linear classification framework.

Experimental results on data obtained from a commercially deployed Voice Search system show that the combination of the proposed features leads to a substantial sentence error rate reduction. In addition, it is shown that personalization features which are very different in nature can successfully complement each other.

References

[1]

Alex Acero, Neal Bernstein, Rob Chambers, Yun-Cheng Ju, Xiao Li, Julian Odell, Patrick Nguyen, Oliver Scholtz and Geoffrey Zweig. 2008. Live Search for Mobile: Web Services by Voice on the Cellphone. ICASSP 2008, March 31 2008-April 4 2008. Las Vegas, NV, USA.

Google Scholar

[2]

Adam L. Berger; Vincent J. Della Pietra; Stephen A. Della Pietra. 1996. A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics, 1996. 22(1): p. 39--72.

Digital Library

Google Scholar

[3]

Abhinandan Das, Mayur Datar and Ashutosh Garg. 2007. Google News Personalization: Scalable Online Collaborative Filtering. WWW 2007/Track: Industrial Practice and Experience May 8--12, 2007. Banff, Alberta, Canada.

Digital Library

Google Scholar

[4]

Sabine Deligne, Satya Dharanipragada, Ramesh Gopinath, Benoit Maison, Peder Olsen and Harry Printz. 2002. A robust high accuracy speech recognition system for mobile applications. Speech and Audio Processing, IEEE Transactions on, Nov 2002, Volume: 10, Issue: 8, On page(s): 551--561.

Google Scholar

[5]

Zhicheng Dou, Ruihua Song, and Ji-Rong Wen. 2007. A large-scale evaluation and analysis of personalized search strategies. In WWW '07: Proceedings of the 16th international conference on World Wide Web, pages 581--590, New York, NY, USA, 2007. ACM Press.

Digital Library

Google Scholar

[6]

Live Search. "http://www.live.com,".

Google Scholar

[7]

Milind Mahajan. 2007. Conditional Maximum-Entropy Training Tool http://research.microsoft.com/enus/downloads/9f199826--49d5--48b6--ba1b-f623ecf36432/.

Google Scholar

[8]

Jaime Teevan, Eytan Adar, Rosie Jones and Michael A. S. Potts. 2007. Information Re-Retrieval: Repeat Queries in Yahoos Logs. SIGIR, 2007.

Digital Library

Google Scholar

Index Terms

Multi-scale personalization for voice search applications
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Speech recognition
  2. Modeling and simulation
    1. Model development and analysis
      1. Model verification and validation
      2. Modeling methodologies
2. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Users and interactive retrieval
      1. Personalization
  2. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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NAACL-Short '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

May 2009

317 pages

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Association for Computational Linguistics

United States

Publication History

Published: 31 May 2009

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Overall Acceptance Rate 21 of 29 submissions, 72%

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Abstract

References

Index Terms

Recommendations

Non-linear frequency scale mapping for voice conversion in text-to-speech system with cepstral description

Improving Automatic Speech Recognizer of Voice Search Using System Combination

Context-aware search personalization with concept preference

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