Combining word and phonetic-code representations for spoken document retrieval

Authors:
Alejandro Reyes-Barragán;Manuel Montes-y-Gómez;Luis Villaseñor-Pineda
Affiliations:
Laboratory of Language Technologies, National Institute of Astrophysics, Optics and Electronics, Puebla, Mexico;Laboratory of Language Technologies, National Institute of Astrophysics, Optics and Electronics, Puebla, Mexico and Department of Computer and Information Sciences, The University of Alabama at Bi ...;Laboratory of Language Technologies, National Institute of Astrophysics, Optics and Electronics, Puebla, Mexico
Venue:
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Year:
2011

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Abstract

The traditional approach for spoken document retrieval (SDR) uses an automatic speech recognizer (ASR) in combination with a word-based information retrieval method. This approach has only showed limited accuracy, partially because ASR systems tend to produce transcriptions of spontaneous speech with significant word error rate. In order to overcome such limitation we propose a method which uses word and phonetic-code representations in collaboration. The idea of this combination is to reduce the impact of transcription errors in the processing of some (presumably complex) queries by representing words with similar pronunciations through the same phonetic code. Experimental results on the CLEF-CLSR-2007 corpus are encouraging; the proposed hybrid method improved the mean average precision and the number of retrieved relevant documents from the traditional word-based approach by 3% and 7% respectively.