Emotional Speaker Identification by Humans and Machines
نویسندگان
چکیده
This paper concerns the problem of the effect of emotion change on human and machine for speaker identification. A contrasting experiment is carried out between Automatic Speaker Identification (ASI) system (applying GMM-UBM and Emotional Factor Analysis (EFA) algorithm)and aural system on emotional speech corpus MASC. The experimental result is similar to that in channel-mismatched condition, i.e. the ASI system is much better than the single listener, especially when emotion compensation algorithm EFA is applied. Meanwhile, fusion of multiple listeners can significantly improve the aural system performance by 23.86% and outperform the ASI system.
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