• DocumentCode
    1550660
  • Title

    Interdependencies among Voice Source Parameters in Emotional Speech

  • Author

    Sundberg, Johan ; Patel, Sona ; Björkner, Eva ; Scherer, Klaus R.

  • Author_Institution
    Dept. of Speech, KTH R. Inst. of Technol., Stockholm, Sweden
  • Volume
    2
  • Issue
    3
  • fYear
    2011
  • Firstpage
    162
  • Lastpage
    174
  • Abstract
    Emotions have strong effects on the voice production mechanisms and consequently on voice characteristics. The magnitude of these effects, measured using voice source parameters, and the interdependencies among parameters have not been examined. To better understand these relationships, voice characteristics were analyzed in 10 actors´ productions of a sustained/a/vowel in five emotions. Twelve acoustic parameters were studied and grouped according to their physiological backgrounds, three related to subglottal pressure, five related to the transglottal airflow waveform derived from inverse filtering the audio signal, and four related to vocal fold vibration. Each emotion appeared to possess a specific combination of acoustic parameters reflecting a specific mixture of physiologic voice control parameters. Features related to subglottal pressure showed strong within-group and between-group correlations, demonstrating the importance of accounting for vocal loudness in voice analyses. Multiple discriminant analysis revealed that a parameter selection that was based, in a principled fashion, on production processes could yield rather satisfactory discrimination outcomes (87.1 percent based on 12 parameters and 78 percent based on three parameters). The results of this study suggest that systems to automatically detect emotions use a hypothesis-driven approach to selecting parameters that directly reflect the physiological parameters underlying voice and speech production.
  • Keywords
    behavioural sciences computing; emotion recognition; speech recognition; emotional speech; hypothesis-driven approach; inverse filtering; physiologic voice control parameters; physiological backgrounds; transglottal airflow waveform; vocal fold vibration; voice source parameters; Acoustics; Filtering; Physiology; Quantum cascade lasers; Semantics; Sensors; Speech processing; Paralanguage analysis; affect sensing and analysis; affective computing; vocal physiology.; voice source;
  • fLanguage
    English
  • Journal_Title
    Affective Computing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3045
  • Type

    jour

  • DOI
    10.1109/T-AFFC.2011.14
  • Filename
    5871584