Abstract

As research in speech processing has matured, attention has gradually shifted from linguistic-related applications such as speech recognition towards paralinguistic speech processing problems, in particular the recognition of speaker identity, language, emotion, gender, and age. Determination of a speaker’s emotion or mental state is a particularly challenging problem, in view of the significant variability in its expression posed by linguistic, contextual, and speaker-specific characteristics within speech. In response, a range of signal processing and pattern recognition methods have been developed in recent years.
Recognition of emotion and mental state from speech is a fundamentally multidisciplinary field, comprising contributions from psychology, speech science, linguistics,(cooccurring) nonverbal communication, machine learning, artificial intelligence and signal processing, among others. Some of the key …

Date

2012

Authors

Julien Epps, Roddy Cowie, Shrikanth Narayanan, Björn Schuller, Jianhua Tao

Journal

EURASIP Journal on Advances in Signal Processing

Volume

2012

Issue

1

Pages

15

Publisher

Springer International Publishing