• 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. Reduction of Subjective Listening Effort for TV Broadcast Signals with Recurrent Neural Networks
 
  • Details
  • Full
Options
2021
Journal Article
Title

Reduction of Subjective Listening Effort for TV Broadcast Signals with Recurrent Neural Networks

Abstract
Listening to the audio of TV broadcast signals can be challenging for hearing-impaired as well as normal-hearing listeners, especially when background sounds are prominent or too loud compared to the speech signal. This can result in a reduced satisfaction and increased listening effort of the listeners. Since the broadcast sound is usually premixed, we perform a subjective evaluation for quantifying the potential of speech enhancement systems based on audio source separation and recurrent neural networks (RNN). Recently, RNNs have shown promising resultsin the context of sound source separation and real-time signal processing. In this paper, we separate the speech from the background signals and remix the separated sounds at a higher signal-to-noise ratio. This differs from classic speech enhancement, where usually only the extracted speech signal is exploited. The subjective evaluation with 20 normal-hearing subjects on real TV-broadcast material shows that our proposed enhancement system is able to reduce the listening effort by around 2 points on a 13-point listening effort rating scale and increases the perceived sound quality compared to the original mixture.
Author(s)
Westhausen, Nils Laurens
Huber, Rainer  
Baumgartner, Hannah
Sinha, Ragini  
Rennies, Jan  
Meyer, Bernd T.
Journal
IEEE ACM transactions on audio, speech, and language processing  
Open Access
DOI
10.1109/TASLP.2021.3126931
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024