Paper: Automatic Estimation of Word Significance oriented for Speech-based Information Retrieval

ACL ID I08-1027
Title Automatic Estimation of Word Significance oriented for Speech-based Information Retrieval
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

Automatic estimation of word significance oriented for speech-based Information Re- trieval (IR) is addressed. Since the sig- nificance of words differs in IR, automatic speech recognition (ASR) performance has been evaluated based on weighted word er- ror rate (WWER), which gives a weight on errors from the viewpoint of IR, instead of word error rate (WER), which treats all words uniformly. A decoding strategy that minimizes WWER based on a Minimum Bayes-Risk framework has been shown, and the reduction of errors on both ASR and IR has been reported. In this paper, we propose an automatic estimation method for word significance (weights) based on its influence on IR. Specifically, weights are estimated so that evaluation measures of ASR and IR are equivalent. We apply the proposed method t...