Abstract
This paper concerns the problem of the effect of emotional change on humans and machines 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 make it outperform the ASI system. © 2011 Springer-Verlag.
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Yang, Y., Chen, L., & Wang, W. (2011). Emotional speaker identification by humans and machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7098 LNCS, pp. 167–173). https://doi.org/10.1007/978-3-642-25449-9_21
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