Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97783
Title: A vector-based approach to broadcast audio database indexing and retrieval
Authors: Wang, Lei
Li, Haizhou
Chng, Eng Siong
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2007
Source: Wang, L., Li, H., & Chng, E. S. (2007). A vector-based approach to broadcast audio database indexing and retrieval. 2007 IEEE International Conference on Multimedia and Expo, pp512-515.
Abstract: This paper proposes a novel framework to index and retrieve audio content from broadcast database that contains both speech and music. In this framework, we model the acoustic events using hidden Markov models, which are then used to decode the audio content. The decoding results in the form of acoustic token sequence and acoustic lattice are used to generate features for indexing and retrieval with the vector space model. Experiments were carried out on the TRECVID database and the results showed that the proposed framework is effective in audio information retrieval. The results also showed that the features generated from the acoustic lattice provide more accurate information than token sequence.
URI: https://hdl.handle.net/10356/97783
http://hdl.handle.net/10220/17345
DOI: 10.1109/ICME.2007.4284699
Rights: © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published version of this article is available at http://dx.doi.org/10.1109/ICME.2007.4284699
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers
SPMS Conference Papers

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