On the use of automatic speech recognition for spoken information retrieval from video databases

Abstract

This document describes the realization of a spoken information retrieval system and its application to words search in an indexed video database. The system uses an automatic speech recognition (ASR) software to convert the audio signal of a video file into a transcript file and then a document indexing tool to index this transcripted file. Then, a spoken query, uttered by any user, is presented to the ASR to decode the audio signal and propose a hypothesis that is later used to formulate a query to the indexed database. The final outcome of the system is a list of video frame tags containing the audio correspondent to the spoken query. The speech recognition system achieved less than 15% Word Error Rate (WER) and its combined operation with the document indexing system showed outstanding performance with spoken queries. © Springer-Verlag 2004.