• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. Using a blind EC mechanism for modelling the interaction between binaural and temporal speech processing
 
  • Details
  • Full
Options
2022
Journal Article
Title

Using a blind EC mechanism for modelling the interaction between binaural and temporal speech processing

Abstract
We reanalyzed a study that investigated binaural and temporal integration of speech reflections with different amplitudes, delays, and interaural phase differences. We used a blind binaural speech intelligibility model (bBSIM), applying an equalization-cancellation process for modeling binaural release from masking. bBSIM is blind, as it requires only the mixed binaural speech and noise signals and no auxiliary information about the listening conditions. bBSIM was combined with two non-blind back-ends: The speech intelligibility index (SII) and the speech transmission index (STI) resulting in hybrid-models. Furthermore, bBSIM was combined with the non-intrusive short-time objective intelligibility (NI-STOI) resulting in a fully blind model. The fully non-blind reference model used in the previous study achieved the best prediction accuracy (R2 = 0.91 and RMSE = 1 dB). The fully blind model yielded a coefficient of determination (R2 = 0.87) similar to that of the reference model but also the highest root mean square error of the models tested in this study (RMSE = 4.4 dB). By adjusting the binaural processing errors of bBSIM as done in the reference model, the RMSE could be decreased to 1.9 dB. Furthermore, in this study, the dynamic range of the SII had to be adjusted to predict the low SRTs of the speech material used.
Author(s)
Röttges, Saskia
Hauth, Christopher F.
Rennies, Jan  
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
Brand, Thomas  
Journal
Acta Acustica  
Open Access
DOI
10.1051/aacus/2022009
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
Keyword(s)
  • Speech intelligibility prediction

  • Temporal processing

  • Binaural processing

  • Auditory model

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024