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A Multiresolution-Based Fusion Strategy for Improving Speech Emotion Recognition Efficiency

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Mobile, Secure, and Programmable Networking (MSPN 2019)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11557))

Abstract

This paper presents a multiresolution-based feature extraction for speech emotion recognition in unconstrained environments. In the proposed approach, Mel Frequency Cepstral Coefficients (MFCC) are derived from Discrete Wavelet Transform (DWT) sub-band coefficients. The extracted features are further combined with conventional MFCCs and pitch-based features to form the final feature vector. Linear Discriminant Analysis (LDA) is used to reduce the dimension of the resulting features set prior to Naive Bayes classification. To assess the performance of the proposed approach in unconstrained environments, noisy speech data are generated by adding real world noises to clean speech signals from the Berlin German Emotional Database (EMO-DB) The proposal is also tested through speaker-dependent and speaker-independent experiments. The overall performance results show improvement in speech emotion detection over baselines.

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Author information

Authors and Affiliations

  1. Team Networks, Telecoms & Multimedia, LIM@II-FSTM, B.P. 146, 20650, Mohammedia, Morocco

    Sara Sekkate, Mohammed Khalil & Abdellah Adib

  2. COSIM Laboratory, Higher School of Communications of Tunis, Carthage University, Route de Raoued Km 3.5, Cité El Ghazala, 2083, Ariana, Tunisia

    Sofia Ben Jebara

Authors
  1. Sara Sekkate
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  2. Mohammed Khalil
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  3. Abdellah Adib
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  4. Sofia Ben Jebara
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Corresponding author

Correspondence to Sara Sekkate .

Editor information

Editors and Affiliations

  1. Télécom SudParis, Évry, France

    Éric Renault

  2. Conservatoire National des Arts et Métiers, Paris, France

    Selma Boumerdassi

  3. Hassan II Mohammedia University, Mohammedia, Morocco

    Cherkaoui Leghris

  4. Conservatoire National des Arts et Métiers, Paris, France

    Samia Bouzefrane

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Sekkate, S., Khalil, M., Adib, A., Ben Jebara, S. (2019). A Multiresolution-Based Fusion Strategy for Improving Speech Emotion Recognition Efficiency. In: Renault, É., Boumerdassi, S., Leghris, C., Bouzefrane, S. (eds) Mobile, Secure, and Programmable Networking. MSPN 2019. Lecture Notes in Computer Science(), vol 11557. Springer, Cham. https://doi.org/10.1007/978-3-030-22885-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-22885-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22884-2

  • Online ISBN: 978-3-030-22885-9

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