Detecting the instant of emotion change from speech using a martingale framework | IEEE Conference Publication | IEEE Xplore

Detecting the instant of emotion change from speech using a martingale framework


Abstract:

Towards a better understanding of emotion in speech, it is important to understand how emotion changes and when it changes. Recognizing emotions using pre-segmented speec...Show More

Abstract:

Towards a better understanding of emotion in speech, it is important to understand how emotion changes and when it changes. Recognizing emotions using pre-segmented speech utterances results in a loss in continuity of emotions and does not provide insights into emotion changes. In this paper, we propose an investigation into emotion change detection from the perspective of exchangeability of data points observed sequentially using a martingale framework. Within the framework, a per-frame GMM likelihood based approach is proposed as a measure of strangeness from a particular emotion class. Experimental results on the IEMOCAP database demonstrate that the proposed martingale framework offers significant improvements over the baseline GLR method for detecting emotion changes not only between neutral and emotional speech, but also between positive and negative classes along the arousal and valence emotion dimensions.
Date of Conference: 20-25 March 2016
Date Added to IEEE Xplore: 19 May 2016
ISBN Information:
Electronic ISSN: 2379-190X
Conference Location: Shanghai, China

References

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