The Cambridge University spoken document retrieval system

Authors:
S. E. Johnson;P. Jourlin;G. L. Moore;K. S. Jones;P. C. Woodland
Affiliations:
Dept. of Eng., Cambridge Univ., UK;-;-;-;-
Venue:
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Year:
1999

Citing 0
Cited 10

Improving retrieval on imperfect speech transcriptions (poster abstract)

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Thematic indexing of spoken documents by using self-organizing maps

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Speech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition

Information Retrieval Techniques for Speech Applications [this book is based on the workshop “Information Retrieval Techniques for Speech Applications”, held as part of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in New Orleans, USA, in September 2001].
Clustering of Imperfect Transcripts Using a Novel Similarity Measure

Information Retrieval Techniques for Speech Applications [this book is based on the workshop “Information Retrieval Techniques for Speech Applications”, held as part of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in New Orleans, USA, in September 2001].
VideoQA: question answering on news video

MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Indexing confusion networks for morph-based spoken document retrieval

SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Question-driven segmentation of lecture speech text: Towards intelligent e-learning systems

Journal of the American Society for Information Science and Technology
An Improve to Human Computer Interaction, Recovering Data from Databases Through Spoken Natural Language

ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
The effect of language models on phonetic decoding for spoken term detection

SSCS '09 Proceedings of the third workshop on Searching spontaneous conversational speech
Time-frequency correlation-based missing-feature reconstruction for robust speech recognition in band-restricted conditions

IEEE Transactions on Audio, Speech, and Language Processing

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Abstract

This paper describes the spoken document retrieval system that we have been developing and assesses its performance using automatic transcriptions of about 50 hours of broadcast news data. The recognition engine is based on the HTK broadcast news transcription system and the retrieval engine is based on the techniques developed at City University. 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. The results demonstrate the importance of high accuracy automatic transcription. The final system is currently being evaluated on the 1998 TREC-7 spoken document retrieval task.