Speech Emotion Recognition Using Deep Neural Network Considering Verbal and Nonverbal Speech Sounds

Kun Yi Huang, Chung Hsien Wu, Qian Bei Hong, Ming Hsiang Su, Yi Hsuan Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Speech emotion recognition is becoming increasingly important for many applications. In real-life communication, non-verbal sounds within an utterance also play an important role for people to recognize emotion. In current studies, only few emotion recognition systems considered nonverbal sounds, such as laughter, cries or other emotion interjection, which naturally exists in our daily conversation. In this work, both verbal and nonverbal sounds within an utterance were thus considered for emotion recognition of real-life conversations. Firstly, an SVM-based verbal/nonverbal sound detector was developed. A Prosodic Phrase (PPh) auto-tagger was further employed to extract the verbal/nonverbal segments. For each segment, the emotion and sound features were respectively extracted based on convolutional neural networks (CNNs) and then concatenated to form a CNN-based generic feature vector. Finally, a sequence of CNN-based feature vectors for an entire dialog turn was fed to an attentive long short-term memory (LSTM)-based sequence-to-sequence model to output an emotional sequence as recognition result. Experimental results on the recognition of seven emotional states in the NNIME (The NTHU-NTUA Chinese interactive multimodal emotion corpus) showed that the proposed method achieved a detection accuracy of 52.00% outperforming the traditional methods.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5866-5870
Number of pages5
ISBN (Electronic)9781479981311
DOIs
Publication statusPublished - 2019 May
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 2019 May 122019 May 17

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
CountryUnited Kingdom
CityBrighton
Period19-05-1219-05-17

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All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Huang, K. Y., Wu, C. H., Hong, Q. B., Su, M. H., & Chen, Y. H. (2019). Speech Emotion Recognition Using Deep Neural Network Considering Verbal and Nonverbal Speech Sounds. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 5866-5870). [8682283] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2019.8682283