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INTERSPEECH
2010

Emotion recognition using imperfect speech recognition

10 years 6 months ago
Emotion recognition using imperfect speech recognition
This paper investigates the use of speech-to-text methods for assigning an emotion class to a given speech utterance. Previous work shows that an emotion extracted from text can convey complementary evidence to the information extracted by classifiers based on spectral, or other non-linguistic features. As speech-to-text usually presents significantly more computational effort, in this study we investigate the degree of speechto-text accuracy needed for reliable detection of emotions from an automatically generated transcription of an utterance. We evaluate the use of hypotheses in both training and testing, and compare several classification approaches on the same task. Our results show that emotion recognition performance stays roughly constant as long as word accuracy doesn't fall below a reasonable value, making the use of speech-to-text viable for training of emotion classifiers based on linguistics.
Florian Metze, Anton Batliner, Florian Eyben, Tim
Added 18 May 2011
Updated 18 May 2011
Type Journal
Year 2010
Where INTERSPEECH
Authors Florian Metze, Anton Batliner, Florian Eyben, Tim Polzehl, Björn Schuller, Stefan Steidl
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