Abstract
An automatic content extraction from multimedia files based both on manual and automatic indexing is extensively explored. However, in the domain of musical data, an automatic content description of musical sounds has not been broadly investigated yet and still needs an intensive research. In this paper, spectro-temporal sound representation is used for the purpose of automatic musical instrument recognition. Assuming that musical instruments can be learned in terms of a group of features and also based on them either automatic or manual indexing of an audio file is done, Frame Segment Trees (FS-trees) can be used to identify segments of an audio marked by the same indexes. Telescopic vector trees (TV-trees) are known from their applications in text processing and recently in data clustering algorithms. In this paper, we use them jointly with FS-trees to construct a new Query Answering System (QAS) for audio data. Audio segments are returned by QAS as answers to user queries. Heuristic strategy to build adaptable TV-trees is proposed.
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Wieczorkowska, A.A., Raś, Z.W., Tsay, LS. (2003). Representing Audio Data by FS-Trees and Adaptable TV-Trees. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_19
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DOI: https://doi.org/10.1007/978-3-540-39592-8_19
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