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@misc{950758, author = {Volný, Petr and Novák, David and Zezula, Pavel}, address = {Brno}, keywords = {audio retrieval; subsequnce matching; similarity search; time series}, language = {eng}, location = {Brno}, publisher = {Faculty of Informatics, Masaryk University, Brno}, title = {Employing Subsequence Matching in Audio Data Processing}, url = {http://www.fi.muni.cz/reports/files/2011/FIMU-RS-2011-04.pdf}, year = {2011} }
TY - GEN ID - 950758 AU - Volný, Petr - Novák, David - Zezula, Pavel PY - 2011 TI - Employing Subsequence Matching in Audio Data Processing VL - FIMU-RS-2011-04 PB - Faculty of Informatics, Masaryk University, Brno CY - Brno KW - audio retrieval KW - subsequnce matching KW - similarity search KW - time series UR - http://www.fi.muni.cz/reports/files/2011/FIMU-RS-2011-04.pdf L2 - http://www.fi.muni.cz/reports/files/2011/FIMU-RS-2011-04.pdf N2 - We overview current problems of audio retrieval and time-series subsequence matching. We discuss the usage of subsequence matching approaches in audio data processing, especially in automatic speech recognition (ASR) area and we aim at improving performance of the retrieval process. To overcome the problems known from the time-series area like the occurrence of implementation bias and data bias we present a Subsequence Matching Framework as a tool for fast prototyping, building, and testing similarity search subsequence matching applications. The framework is build on top of MESSIF (Metric Similarity Search Implementation Framework) and thus the subsequence matching algorithms can exploit advanced similarity indexes in order to significantly increase their query processing performance. To prove our concept we provide a design of query-by-example spoken term detection type of application with the usage of phonetic posteriograms and subsequence matching approach. ER -
VOLNÝ, Petr, David NOVÁK and Pavel ZEZULA. \textit{Employing Subsequence Matching in Audio Data Processing}. Brno: Faculty of Informatics, Masaryk University, Brno, 2011. FIMU-RS-2011-04.
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