Emotion discrimination with increasing time windows in spoken Finnish
نویسندگان
چکیده
A study of the automatic discrimination of emotion in three different time windows of speech is presented. A large corpus of acted emotional speech in Finnish was collected in five emotional states: neutral, sadness, joy, anger and tenderness. Automatic emotion discrimination tests were performed in speaker-independent scenarios using kNN classifiers with sequential forwards-backwards floating search feature selection algorithm. Three time windows were used in the stimuli: vowel, utterance and monologue. Human emotion discrimination tests, i.e. listening tests, were performed to obtain baseline data. The results indicate, firstly, that the average emotion discrimination performance levels did not differ at all for the human listeners vs. the computer at the vowel level. However, for the longer speech units, the human listeners did better in the discrimination tasks, with a very clear difference at the monologue level. It can be concluded that, in emotion discrimination, the human listener can utilize more prosodic cues than the computer when the speech unit increases (durationally and syntac-
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