Robust techniques for organizing and retrieving spoken documents

Authors:
James Allan
Affiliations:
Center for Information Retrieval, Department of Computer Science, University of Massachusetts, Amherst, MA
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2003

Citing 16
Cited 4

Query expansion using local and global document analysis

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Open-vocabulary speech indexing for voice and video mail retrieval

MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Statistical methods for speech recognition

Statistical methods for speech recognition
Local Feedback in Full-Text Retrieval Systems

Journal of the ACM (JACM)
TextFinder: An Automatic System to Detect and Recognize Text In Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the effectiveness of information retrieval with local context analysis

ACM Transactions on Information Systems (TOIS)
Evaluating evaluation measure stability

SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
First story detection in TDT is hard

Proceedings of the ninth international conference on Information and knowledge management
Relevance based language models

Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Text Segmentation by Topic

ECDL '97 Proceedings of the First European Conference on Research and Advanced Technology for Digital Libraries
Topic detection and tracking evaluation overview

Topic detection and tracking
Multi-strategy learning for topic detection and tracking: a joint report of CMU approaches to multilingual TDT

Topic detection and tracking
Explorations within topic tracking and detection

Topic detection and tracking
Speech in noisy environments (spine) adds new dimension to speech recognition R&D

HLT '02 Proceedings of the second international conference on Human Language Technology Research
Relevance models for topic detection and tracking

HLT '02 Proceedings of the second international conference on Human Language Technology Research
Statistical answer-type identification in open-domain question answering

HLT '02 Proceedings of the second international conference on Human Language Technology Research

A lattice-based approach to query-by-example spoken document retrieval

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Investigating the Global Semantic Impact of Speech Recognition Error on Spoken Content Collections

ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Combining word and phonetic-code representations for spoken document retrieval

CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Spoken Content Retrieval: A Survey of Techniques and Technologies

Foundations and Trends in Information Retrieval

Quantified Score

Hi-index	0.00

Visualization

Abstract

Information retrieval tasks such as document retrieval and topic detection and tracking (TDT) show little degradation when applied to speech recognizer output. We claim that the robustness of the process is because of inherent redundancy in the problem: not only are words repeated, but semantically related words also provide support. We show how document and query expansion can enhance that redundancy and make document retrieval robust to speech recognition errors. We show that the same effect is true for TDT's tracking task, but that recognizer errors are more of an issue for new event and story link detection.