Publication | Closed Access
Robust minimum statistics project coefficients feature for acoustic environment recognition
20
Citations
20
References
2014
Year
Unknown Venue
AeroacousticsEngineeringAcoustic ModelingAcoustic Environment RecognitionSpeech RecognitionData SciencePattern RecognitionAudio AnalysisNoiseRobust Speech RecognitionAcoustic Signal ProcessingStatisticsHealth SciencesInverse ProblemsComputer ScienceSignal ProcessingMspc FeatureSpeech ProcessingForeground Sound
Acoustic environment recognition has been widely used in many applications, and is a considerable difficult problem for the real-life and complex environment. This paper proposes a novel feature, named minimum statistics project coefficients (MSPC), and intents to solve this problem. The MSPC feature is extracted from the background sound which is more robust than the foreground sound for the task of acoustic environment recognition. Experimental results show the outstanding performance of the MSPC feature compared with the conventional acoustic features, especially in very complex acoustic environments.
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