Using statistical testing in the evaluation of retrieval experiments
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Effects of out of vocabulary words in spoken document retrieval (poster session)
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Integration of continuous speech recognition and information retrieval for mutually optimal performance
Subword-based approaches for spoken document retrieval
Subword-based approaches for spoken document retrieval
Spoken document retrieval from call-center conversations
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The Cambridge University spoken document retrieval system
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Word and sub-word indexing approaches for reducing the effects of OOV queries on spoken audio
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Spoken information retrieval for turkish broadcast news
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Statistical lattice-based spoken document retrieval
ACM Transactions on Information Systems (TOIS)
Performance analysis for lattice-based speech indexing approaches using words and subword units
IEEE Transactions on Audio, Speech, and Language Processing
ACM Transactions on Speech and Language Processing (TSLP)
Direct posterior confidence for out-of-vocabulary spoken term detection
ACM Transactions on Information Systems (TOIS)
Spoken Content Retrieval: A Survey of Techniques and Technologies
Foundations and Trends in Information Retrieval
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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In this paper, we investigate methods for improving the performance of morph-based spoken document retrieval in Finnish by extracting relevant index terms from confusion networks. Our approach uses morpheme-like subword units ("morphs") for recognition and indexing. This alleviates the problem of out-of-vocabulary words, especially with inflectional languages like Finnish. Confusion networks offer a convenient representation of alternative recognition candidates by aligning mutually exclusive terms and by giving the posterior probability of each term. The rank of the competing terms and their posterior probability is used to estimate term frequency for indexing. Comparing against 1-best recognizer transcripts, we show that retrieval effectiveness is significantly improved. Finally, the effect of pruning in recognition is analyzed, showing that when recognition speed is increased, the reduction in retrieval performance due to the increase in the 1-best error rate can be compensated by using confusion networks.