On NoMatchs, NoInputs and BargeIns: Do Non-Acoustic Features Support Anger Detection?
نویسندگان
چکیده
Most studies on speech-based emotion recognition are based on prosodic and acoustic features, only employing artificial acted corpora where the results cannot be generalized to telephone-based speech applications. In contrast, we present an approach based on utterances from 1,911 calls from a deployed telephone-based speech application, taking advantage of additional dialogue features, NLU features and ASR features that are incorporated into the emotion recognition process. Depending on the task, non-acoustic features add 2.3% in classification accuracy compared to using only acoustic features.
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