@inproceedings{diener2018investigating,
  title        = {Investigating Objective Intelligibility in Real-Time EMG-to-Speech Conversion},
  author       = {Lorenz Diener and Tanja Schultz},
  year         = 2018,
  month        = sep,
  booktitle    = {{INTERSPEECH} 2018 -- 19th Annual Conference of the International Speech
    Communication Association},
  abstract     = {This paper presents an analysis of the influence of various system parameters on
    the output quality of our neural network based real-time EMG-to-Speech conversion system. This
    EMG-to-Speech system allows for the direct conversion of facial surface electromyographic
    signals into audible speech in real time, allowing for a closed-loop setup where users get
    direct audio feedback. Such a setup opens new avenues for research and applications through
    co-adaptation approaches. In this paper, we evaluate the influence of several parameters on the
    output quality, such as time context, EMG-Audio delay, network-, training data- and Mel
    spectrogram size. The resulting output quality is evaluated based on the objective output
    quality measure STOI.},
  url          = {https://halcy.de/cites/pdf/diener2018investigating.pdf},
}