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Spectrum Modification for Emotional Speech Synthesis

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Multimodal Signals: Cognitive and Algorithmic Issues

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5398))

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Abstract

Emotional state of a speaker is accompanied by physiological changes affecting respiration, phonation, and articulation. These changes are manifested mainly in prosodic patterns of F0, energy, and duration, but also in segmental parameters of speech spectrum. Therefore, our new emotional speech synthesis method is supplemented with spectrum modification. It comprises non-linear frequency scale transformation of speech spectral envelope, filtering for emphasizing low or high frequency range, and controlling of spectral noise by spectral flatness measure according to knowledge of psychological and phonetic research. The proposed spectral modification is combined with linear modification of F0 mean, F0 range, energy, and duration. Speech resynthesis with applied modification that should represent joy, anger and sadness is evaluated by a listening test.

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References

  1. Scherer, K.R.: Vocal Communication of Emotion: A Review of Research Paradigms. Speech Communication 40, 227–256 (2003)

    Article  MATH  Google Scholar 

  2. Nwe, T.L., Foo, S.W., De Silva, L.C.: Speech Emotion Recognition Using Hidden Markov Models. Speech Communication 41, 603–623 (2003)

    Article  Google Scholar 

  3. Ververidis, D., Kotropoulos, C.: Emotional Speech Recognition: Resources, Features, and Methods. Speech Communication 48, 1162–1181 (2006)

    Article  Google Scholar 

  4. Shami, M., Verhelst, W.: An Evaluation of the Robustness of Existing Supervised Machine Learning Approaches to the Classification of Emotions in Speech. Speech Communication 49, 201–212 (2007)

    Article  Google Scholar 

  5. Tóth, S.L., Sztahó, D., Vicsi, K.: Speech Emotion Perception by Human and Machine. In: Esposito, A., Bourbakis, N.G., Avouris, N., Hatzilygeroudis, I. (eds.) Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction. LNCS (LNAI), vol. 5042, pp. 213–224. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Murray, I.R., Arnott, J.L.: Applying an Analysis of Acted Vocal Emotions to Improve the Simulation of Synthetic Speech. Computer Speech and Language 22, 107–129 (2008)

    Article  Google Scholar 

  7. Bänziger, T., Scherer, K.R.: The Role of Intonation in Emotional Expressions. Speech Communication 46, 252–267 (2005)

    Article  Google Scholar 

  8. Vích, R.: Cepstral Speech Model, Padé Approximation, Excitation, and Gain Matching in Cepstral Speech Synthesis. In: Proceedings of Biosignal, Brno, pp. 77–82 (2000)

    Google Scholar 

  9. Fant, G.: Acoustical Analysis of Speech. In: Crocker, M.J. (ed.) Encyclopedia of Acoustics, pp. 1589–1598. John Wiley & Sons, Chichester (1997)

    Chapter  Google Scholar 

  10. Fant, G.: Speech Acoustics and Phonetics. Kluwer Academic Publishers, Dordrecht (2004)

    Google Scholar 

  11. Laroche, J.: Time and Pitch Scale Modification of Audio Signals. In: Kahrs, M., Brandenburg, K. (eds.) Applications of Digital Signal Processing to Audio and Acoustics, pp. 279–309. Kluwer Academic Publishers, Dordrecht (2001)

    Google Scholar 

  12. Morrison, D., Wang, R., De Silva, L.C.: Ensemble Methods for Spoken Emotion Recognition in Call-Centres. Speech Communication 49, 98–112 (2007)

    Article  Google Scholar 

  13. Dutilleux, P., Zölzer, U.: Filters. In: Zölzer, U. (ed.) DAFX – Digital Audio Effects, pp. 31–62. John Wiley & Sons, Chichester (2002)

    Google Scholar 

  14. Drioli, C., Tisato, G., Cosi, P., Tesser, F.: Emotions and Voice Quality: Experiments with Sinusoidal Modeling. In: Proceedings of Voice Quality, Geneva, pp. 127–132 (2003)

    Google Scholar 

  15. Hirose, K., Sato, K., Asano, Y., Minematsu, N.: Synthesis of F0 Contours Using Generation Process Model Parameters Predicted form Unlabeled Corpora: Application to Emotional Speech Synthesis. Speech Communication 46, 385–404 (2005)

    Article  Google Scholar 

  16. Navas, E., Hernáez, I., Luengo, I.: An Objective and Subjective Study of the Role of Semantics and Prosodic Features in Building Corpora for Emotional TTS. IEEE Transactions on Audio, Speech, and Language Processing 14, 1117–1127 (2006)

    Article  Google Scholar 

  17. Cabral, J.P., Oliveira, L.C.: EmoVoice: A System to Generate Emotions in Speech. In: Proceedings of Interspeech – ICSLP. pp. 1798–1801. Pittsburgh (2006)

    Google Scholar 

  18. Přibil, J., Přibilová, A.: Emotional Style Conversion in the TTS System with Cepstral Description. In: Esposito, A., Faundez-Zanuy, M., Keller, E., Marinaro, M. (eds.) COST Action 2102. LNCS (LNAI), vol. 4775, pp. 65–73. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  19. Přibilová, A., Přibil, J.: Non-Linear Frequency Scale Mapping for Voice Conversion in Text-to-Speech System with Cepstral Description. Speech Communication 48, 1691–1703 (2006)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Radio Electronics, Slovak University of Technology, Ilkovičova 3, SK-812 19, Bratislava, Slovakia

    Anna Přibilová

  2. Institute of Photonics and Electronics, Academy of Sciences of the Czech Republic, Chaberská 57, CZ-182 51, Prague, Czech Republic

    Jiří Přibil

Authors
  1. Anna Přibilová
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  2. Jiří Přibil
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Editor information

Editors and Affiliations

  1. Department of Psychology, Second University of Naples, and IIASS, Via Pellegrino 19, 84019, Vietri sul Mare (SA), Italy

    Anna Esposito

  2. Department of Computing Science & Mathematics, University of Stirling, FK9 4LA, Stirling, Scotland, UK

    Amir Hussain

  3. Dipartimento di Fisica “E.R. Caianiello”, Università degli Studi di Salerno, Italy and IIASS, Via S. Allende, 84081, Baronissi (SA), Italy

    Maria Marinaro

  4. Dip. di Ingegneria dell’ Informazione, Seconda Università di Napoli, Via Roma 29, 81031, Aversa (CE), Italy

    Raffaele Martone

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Přibilová, A., Přibil, J. (2009). Spectrum Modification for Emotional Speech Synthesis. In: Esposito, A., Hussain, A., Marinaro, M., Martone, R. (eds) Multimodal Signals: Cognitive and Algorithmic Issues. Lecture Notes in Computer Science(), vol 5398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00525-1_23

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  • DOI: https://doi.org/10.1007/978-3-642-00525-1_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00524-4

  • Online ISBN: 978-3-642-00525-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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