Subword-based approaches for spoken document retrieval
Subword-based approaches for spoken document retrieval
Vocabulary independent spoken term detection
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Effect of pronounciations on OOV queries in spoken term detection
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Rapid Yet Accurate Speech Indexing Using Dynamic Match Lattice Spotting
IEEE Transactions on Audio, Speech, and Language Processing
Direct posterior confidence for out-of-vocabulary spoken term detection
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Information Systems (TOIS)
| Hi-index | 0.00 |
Query-by-example (QbE) spoken term detection (STD) is necessary for low-resource scenarios where training material is hardly available and word-based speech recognition systems cannot be employed. We present two novel contributions to QbE STD: the first introduces several criteria to select the optimal example used as query throughout the search system. The second presents a novel feature level example combination to construct a more robust query used during the search. Experiments, tested on with-in language and cross-lingual QbE STD setups, show a significant improvement when the query is selected according to an optimal criterion over when the query is selected randomly for both setups and a significant improvement when several examples are combined to build the input query for the search system compared with the use of the single best example. They also show comparable performance to that of a state-of-the-art acoustic keyword spotting system.