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This paper deals with comparison of sub-word based methods for spoken term detection (STD) task and phone recognition. The sub-word units are needed for search for out-of-vocabulary words. We compared words, phones and multigrams. The maximal length and pruning of multigrams were investigated first. Then two constrained methods of multigram training were proposed. We evaluated on the NIST STD06 dev-set...
We examine the task of spoken term detection in Chinese spontaneous speech with a lattice-based approach. We first compare lattices generated with different units: word, character, tonal and toneless syllables, and also lattices converted from one unit to another unit. Then we combine lattices from multiple systems into a single lattice. By fully exploiting the redundant information in the combined...
Enterprise-scale search engines are generally designed for linear text. Linear text is suboptimal for audio search, where accuracy can be significantly improved if the search includes alternate recognition candidates, commonly represented as word lattices. We propose two methods to enable text indexers to approximately index lattices with little or no code change: "TMI" (Time-based Merging...
with toneless-syllable lattices converted from word lattices. Further improvement is achieved by lattice post-processing and system combination. Our best system has an accuracy of 80.2% on a keyword spotting task.
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