A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
This paper investigates the automatic recognition of emotion from spoken words by vector space modeling vs. string kernels which have not been investigated in this respect, yet. Apart from the spoken content directly, we integrate Part-of-Speech and higher semantic tagging in our analyses. As opposed to most works in the field, we evaluate the performance with an ASR engine in the loop. Extensive experiments are run on the FAU Aibo Emotion Corpus of 4k spontaneous emotional child-robotdoi:10.1109/icassp.2009.4960651 dblp:conf/icassp/SchullerBSS09 fatcat:47l3qolvnnhedjsyoykemsdzvq