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    %0 Conference Proceedings
    %A Obin, Nicolas
    %A Roebel, Xavier
    %A Bachman, Grégoire
    %T On Automatic Voice Casting for Expressive Speech: Speaker Recognition vs. Speech Classification
    %D 2014
    %B IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),
    %C Florence
    %F Obin14c
    %K voice casting
    %K voice similarity
    %K speaker recognition
    %K speech classification
    %X This paper presents the first large-scale automatic voice casting system, and explores the adaptation of speaker recognition techniques to measure voice similarities. The proposed system is based on the representation of a voice by classes (e.g., age/gender, voice quality, emotion). First, a multi-label system is used to classify speech into classes. Then, the output probabilities for each class are concatenated to form a vector that represents the vocal signature of a speech recording. Finally, a similarity search is performed on the vocal signatures to determine the set of target actors that are the most similar to a speech recording of a source actor. In a subjective experiment conducted in the real-context of voice casting for video games, the multi-label system clearly outperforms standard speaker recognition systems. This indicates evidence that speech classes successfully capture the principal directions that are used in the perception of voice similarity.
    %1 6
    %2 2
    %U http://architexte.ircam.fr/textes/Obin14c/
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