PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Retrieving speech correctly despite the recognition errors
Mikko Kurimo and Ville Turunen
In: 2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms(2005).

Abstract

This work studies ways to recover from speech recognition errors in retrieving spoken documents. The methods are evaluated by Finnish news reading data using an unlimited vocabulary recognizer with language models for unsupervised morpheme-like units. Recognition errors can naturally be reduced by improving the recognizer, but the focus here is on the attempts to improve the search index more directly, namely by adding new index terms to replace those lost due to recognition errors.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Speech
Information Retrieval & Textual Information Access
ID Code:1060
Deposited By:Mikko Kurimo
Deposited On:29 August 2005