Title :
Minimum Bayes-Risk decoding with presumedword significance for speech based information retrieval
Author :
Shichiri, Takashi ; Nanjo, Hiroaki ; Yoshimi, Takehiko
Author_Institution :
Grad. Sch. of Sci. & Technol., Ryukoku Univ. Seta, Otsu
fDate :
March 31 2008-April 4 2008
Abstract :
This paper addresses automatic speech recognition (ASR) oriented for speech based information retrieval (IR). Since the significance of words differs in IR, in ASR for IR, ASR performance should be evaluated based on weighted word error rate (WWER), which gives a different weight on each word recognition error from the viewpoint of IR, instead of word error rate (WER), which treats all words uniformly. In this paper, we firstly discuss an automatic estimation method of word significance (weights), and then, we perform ASR based on Minimum Bayes-Risk framework using the presumed word significance, and show that the ASR approach that minimizes WWER calculated from the presumed word weighs is effective for speech based IR.
Keywords :
Bayes methods; decoding; information retrieval; speech coding; speech recognition; automatic estimation method; automatic speech recognition; minimum Bayes-risk decoding; presumed word significance; speech based information retrieval; speech processing; weighted word error rate; word recognition error; Automatic speech recognition; Decoding; Degradation; Error analysis; Error correction; Frequency; Indexing; Information retrieval; Speech processing; Speech recognition; Information retrieval; Speech processing; Speech recognition;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4517920