whether or not they are lying) is discovered Cowie et al. Another application is crime detection where the psychological state of criminal suspects (i.e. ( 2011) or help autistic children learn how to recognize more subtle social cues Heni and Hamam ( 2016). These systems can also be used in health domains to monitor and detect the early signs of a depression episode Dickerson et al. For example, negative/positive experience of customers can be automatically detected in remote call centres to evaluate company services or attitude of staff towards customers Batliner et al. These systems have a wide range of applications from human-machine interactions to auto-supervision and control of safety systems Huahu et al. Speech emotion detection systems aim at recognizing the underlying affective state of speakers from their speech signals. In for academic purposes free of charge to provide a baselineįor further research on Persian emotional speech. Vector machine achieves the best results for both gender-independent (58.2 Methods in speech emotion detection task. We also present benchmark results based on common classification According to the kappa measure, theĪgreement". Label the underlying emotional state of utterances and majority voting is used Happiness, sadness and surprise, as well as neutral state. Native-Persian speakers for five basic emotions including anger, fear, Semi-natural utterances, equivalent to 3 hours and 25 minutes of speech dataĮxtracted from online radio plays. Sharif Emotional Speech Database (ShEMO). This paper introduces a large-scale, validated database for Persian called
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