Mixed Feelings About Using Phoneme-Level Models in Emotion Recognition

  • Hannes Pirker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4738)


This study deals with the application of MFCC based models for both the recognition of emotional speech and the recognition of emotions in speech. More specifically it investigates the performance of phone-level models. First, results from performing forced alignment for the phonetic segmentation on GEMEP, a novel multimodal corpus of acted emotional utterances are presented, then the newly acquired segmentations are used for experiments with emotion recognition.


Hide Markov Model Gaussian Mixture Model Emotion Recognition Speech Sound Emotional Speech 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Bänziger, T., Pirker, H., Scherer, K.: GEMEP - GEneva Multimodal Emotion Portrayals: A corpus for the study of multimodal emotional expressions. In: LREC 2006 Workshop Corpora for Research on Emotion and Affect, Genoa, Italy, pp. 15–19 (2006)Google Scholar
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    Young, S., Evermann, G., Kershaw, D., Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V., Woodland, P.: The HTK Book (version 3.4). Cambridge University Engineering Department, Cambridge UK (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hannes Pirker
    • 1
  1. 1.Austrian Research Institute for Artificial Intelligence (OFAI), A-1010 ViennaAustria

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