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Online Speaker Adaptation of an Acoustic Model Using Face Recognition

  • Pavel Campr
  • Aleš Pražák
  • Josef V. Psutka
  • Josef Psutka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8082)

Abstract

We have proposed and evaluated a novel approach for online speaker adaptation of an acoustic model based on face recognition. Instead of traditionally used audio-based speaker identification we investigated the video modality for the task of speaker detection. A simulated on-line transcription created by a Large-Vocabulary Continuous Speech Recognition (LVCSR) system for online subtitling is evaluated utilizing speaker independent acoustic models, gender dependent models and models of particular speakers. In the experiment, the speaker dependent acoustic models were trained offline, and are switched online based on the decision of a face recognizer, which reduced Word Error Rate (WER) by 12% relatively compared to speaker independent baseline system.

Keywords

acoustic model speaker adaptation face recognition multimodal processing automatic speech recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pavel Campr
    • 1
  • Aleš Pražák
    • 2
  • Josef V. Psutka
    • 2
  • Josef Psutka
    • 2
  1. 1.Center for Machine Perception, Department of Cybernetics, Faculty of Electrical EngineeringCzech Technical University in PraguePrague 6Czech Republic
  2. 2.Department of Cybernetics, Faculty of Applied SciencesUniversity of West Bohemia in PilsenPilsenCzech Republic

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