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An experimental study of an audio indexing system for the web.

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TLDR
A speech recognition based audio search engine for indexing spoken documents found on the World Wide Web, focusing on the speech recognition and retrieval aspects, and the results of retrieval experiments demonstrate that the system can index effectively.
Abstract
We have developed a speech recognition based audio search engine for indexing spoken documents found on the World Wide Web Our site (http://wwwcompaqcom/speechbot) indexes around 20 news and talk radio shows covering a wide range of topics, speaking styles and acoustic conditions from a selection of public Web sites with multimedia archives In this paper, we describe our system and its performance, focusing on the speech recognition and retrieval aspects We describe our training procedure in some detail and report our historical error rate since the site launch We also investigate the impact of Out Of Vocabulary (OOV) words Finally we report the results of retrieval experiments which demonstrate that our system can index effectively

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Vocabulary independent spoken term detection

TL;DR: This work presents a vocabulary independent system that can handle arbitrary queries, exploiting the information provided by having both word transcripts and phonetic transcripts, in order to retrieve information from speech data.
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Spoken content retrieval: beyond cascading speech recognition with text retrieval

TL;DR: This overview article is intended to provide a thorough overview of the concepts, principles, approaches, and achievements of major technical contributions along this line of investigation.
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Vocabulary-independent search in spontaneous speech

TL;DR: This work presents a vocabulary-independent system to index and to search rapidly spontaneous speech, and introduces a new method of phonetic word-fragment lattice generation, which uses longer-span language knowledge than a phoneme recognizer.
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Speechbot: an experimental speech-based search engine for multimedia content on the web

TL;DR: This paper uses speech recognition technology to index spoken audio and video files from the World Wide Web when no transcriptions are available, and shows that, even if the transcription is inaccurate, it can still achieve good retrieval performance for typical user queries.
Proceedings ArticleDOI

Fast Vocabulary-Independent Audio Search Using Path-Based Graph Indexing

TL;DR: A fast vocabulary independent audio search approach that operates on phonetic lattices and is suitable for any query, inspired by a general graph indexing method that defines an automatic procedure to select a small number of paths as indexing features, keeping the index size small while allowing fast retrieval of the lattices matching a given query.
References
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Analysis of a Very Large AltaVista Query Log

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1998 TREC-7 Spoken Document Retrieval Track Overview and Results

TL;DR: The 1998 TREC-7 Spoken Document Retrieval (SDR) Track which implemented an evaluation of retrieval of broadcast news excerpts using a combination of automatic speech recognition and information retrieval technologies is described.
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Proceedings ArticleDOI

The Cambridge University spoken document retrieval system

TL;DR: The retrieval performance over a wide range of speech transcription error rates is presented and a number of recognition error metrics that more accurately reflect the impact of transcription errors on retrieval accuracy are defined and computed.