@inproceedings{diener2015codebook,
  title        = {Codebook Clustering for Unit Selection Based EMG-to-Speech Conversion},
  author       = {Diener, Lorenz and Janke, Matthias and Schultz, Tanja},
  year         = 2015,
  month        = sep,
  booktitle    = {{INTERSPEECH} 2015 - 16th Annual Conference of the International Speech
    Communication Association},
  pages        = {2420--2424},
  doi          = {10.21437/Interspeech.2015-523},
  abstract     = {This paper reports on our recent advances in using Unit Selection to directly
    synthesize speech from facial surface electromyographic (EMG) signals generated by movement of
    the articulatory muscles during speech production. We achieve a robust Unit Selection mapping by
    using a more sophisticated unit codebook. This codebook is generated from a set of base units
    using a two stage unit clustering process. The units are first clustered based on the audio and
    afterwards on the EMG feature vectors they cover, and a new codebook is generated using these
    cluster assignments. We evaluate different cluster counts for both stages and revisit our
    evaluation of unit sizes in light of this clustering approach. Our final system achieves a
    significantly better Mel-Cepstral distortion score than the Unit Selection based EMG-to-Speech
    conversion system from our previous work while, due to the reduced codebook size, taking less
    time to perform the conversion.},
  keywords     = {electromyography, silent speech interface, unit selection},
  url          = {https://halcy.de/cites/pdf/diener2015codebook.pdf},
}