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In this paper we report our approaches to accomplishing the very limited resource keyword search (KWS) task in the NIST Open Keyword Search 2015 (OpenKWS15) Evaluation. We devised the methods, first, to attain better acoustic modeling, multilingual and semi-supervised acoustic model training as well as the examplar-based acoustic model training; second, to address the overwhelming out-of-vocabulary...
We propose strategies for a state-of-the-art keyword search (KWS) system developed by the SINGA team in the context of the 2014 NIST Open Keyword Search Evaluation (OpenKWS14) using conversational Tamil provided by the IARPA Babel program. To tackle low-resource challenges and the rich morphological nature of Tamil, we present highlights of our current KWS system, including: (1) Submodular optimization...
In this paper, we propose a partial sequence matching based symbolic search (SS) method for the task of language independent query-by-example spoken term detection. One main drawback of conventional SS approach is the high miss rate for long queries. This is due to high variations in symbol representation of query and search audios, especially in language independent scenario. The successful matching...
In this paper we describe approaches to building our recent Malay broadcast news audio retrieval system. This system contains speech-to-text and keyword search subsystems. The speech-to-text system is built aiming at two folds: hybrid vocabulary recognition to tackle out-of-vocabulary keyword search issue and diversified acoustic modeling for effective system combination in keyword searching afterwards...
System combination (or data fusion1) is known to provide significant improvement for spoken term detection (STD). The key issue of the system combination is how to effectively fuse the various scores of participant systems. Currently, most system combination methods are system and keyword independent, i.e. they use the same arithmetic functions to combine scores for all keywords. Although such strategy...
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