Recognition of Non-Prototypical Emotions in Reverberated and Noisy Speech by Non-Negative Matrix Factorization

Weninger F, Schuller B, Batliner A, Steidl S, Seppi D (2011)


Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2011

Journal

Original Authors: Weninger Felix, Schuller Björn, Batliner Anton, Steidl Stefan, Seppi Dino

Publisher: Hindawi Publishing Corporation / Springer Verlag (Germany) / SpringerOpen

Book Volume: 2011

Pages Range: 1-16

Article Number: 838790

URI: http://downloads.hindawi.com/journals/asp/2011/838790.pdf

DOI: 10.1155/2011/838790

Abstract

We present a comprehensive study on the effect of reverberation and background noise on the recognition of nonprototypical emotions from speech. We carry out our evaluation on a single, well-defined task based on the FAU Aibo Emotion Corpus consisting of spontaneous children's speech, which was used in the INTERSPEECH 2009 Emotion Challenge, the first of its kind. Based on the challenge task, and relying on well-proven methodologies from the speech recognition domain, we derive test scenarios with realistic noise and reverberation conditions, including matched as well as mismatched condition training. As feature extraction based on supervised Nonnegative Matrix Factorization (NMF) has been proposed in automatic speech recognition for enhanced robustness, we introduce and evaluate different kinds of NMF-based features for emotion recognition. We conclude that NMF features can significantly contribute to the robustness of state-of-the-art emotion recognition engines in practical application scenarios where different noise and reverberation conditions have to be faced.

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APA:

Weninger, F., Schuller, B., Batliner, A., Steidl, S., & Seppi, D. (2011). Recognition of Non-Prototypical Emotions in Reverberated and Noisy Speech by Non-Negative Matrix Factorization. EURASIP Journal on Advances in Signal Processing, 2011, 1-16. https://dx.doi.org/10.1155/2011/838790

MLA:

Weninger, Felix, et al. "Recognition of Non-Prototypical Emotions in Reverberated and Noisy Speech by Non-Negative Matrix Factorization." EURASIP Journal on Advances in Signal Processing 2011 (2011): 1-16.

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