Parallel model combination and word recognition in soccer audio
Longton, JH and Jackson, PJB (2008) Parallel model combination and word recognition in soccer audio In: IEEE International Conference on Multimedia and Expo (ICME 2008), 2008-06-23 - 2008-06-26, Hannover, Germany.
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The audio scene from broadcast soccer can be used for identifying highlights from the game. Audio cues derived from these sources provide valuable information about game events, as can the detection of key words used by the commentators. In this paper we interpret the feasibility of incorporating both commentator word recognition and information about the additive background noise in an HMM structure. A limited set of audio cues, which have been extracted from data collected from the 2006 FIFA World Cup, are used to create an extension to the Aurora-2 database. The new database is then tested with various PMC models and compared to the standard baseline, clean and multi-condition training methods. It is found that incorporating SNR and noise type information into the PMC process is beneficial to recognition performance.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Identification Number :||https://doi.org/10.1109/ICME.2008.4607722|
|Uncontrolled Keywords :||Audio indexing, soccer, HMM|
|Additional Information :||
Copyright 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
|Depositing User :||Symplectic Elements|
|Date Deposited :||25 Nov 2011 15:26|
|Last Modified :||23 Sep 2013 18:51|
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