Real-Time Emotion Recognition from Speech Using Echo State Networks

The goal of this work is to investigate real-time emotion recognition in noisy environments. Our approach is to solve this problem using novel recurrent neural networks called echo state networks (ESN). ESNs utilizing the sequential characteristics of biologically motivated modulation spectrum features are easy to train and robust towards noisy real world conditions. The standard Berlin Database of Emotional Speech is used to evaluate the performance of the proposed approach. The experiments reveal promising results overcoming known difficulties and drawbacks of common approaches.

[1]  Valery A. Petrushin,et al.  EMOTION IN SPEECH: RECOGNITION AND APPLICATION TO CALL CENTERS , 1999 .

[2]  Frank Dellaert,et al.  Recognizing emotion in speech , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[3]  Oudeyer Pierre-Yves,et al.  The production and recognition of emotions in speech: features and algorithms , 2003 .

[4]  Malcolm Slaney,et al.  Construction and evaluation of a robust multifeature speech/music discriminator , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Rosalind W. Picard.  Affective Computing , 1997 .

[6]  Misha Pavel,et al.  On the relative importance of various components of the modulation spectrum for automatic speech recognition , 1999, Speech Commun..

[7]  Steven J. Simske,et al.  Recognition of emotions in interactive voice response systems , 2003, INTERSPEECH.

[8]  Zhigang Deng,et al.  Emotion recognition based on phoneme classes , 2004, INTERSPEECH.

[9]  Ryohei Nakatsu,et al.  Emotion Recognition in Speech Using Neural Networks , 2000, Neural Computing & Applications.

[10]  R. Plomp,et al.  Effect of reducing slow temporal modulations on speech reception. , 1994, The Journal of the Acoustical Society of America.

[11]  Lori Lamel,et al.  Challenges in real-life emotion annotation and machine learning based detection , 2005, Neural Networks.

[12]  J. G. Taylor,et al.  Emotion recognition in human-computer interaction , 2005, Neural Networks.

[13]  George N. Votsis,et al.  Emotion recognition in human-computer interaction , 2001, IEEE Signal Process. Mag..

[14]  Astrid Paeschke,et al.  A database of German emotional speech , 2005, INTERSPEECH.

[15]  H. Hermansky,et al.  The modulation spectrum in the automatic recognition of speech , 1997, 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings.

[16]  G. Palm,et al.  Classifier fusion for emotion recognition from speech , 2007 .