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Masking Speech Contents by Random Splicing: is Emotional Expression Preserved?

AuthorsBurkhardt Felix, Derington Anna, Kahlau Matthias, Scherer Klaus, Eyben Florian, Schuller, Bjorn
TitleMasking Speech Contents by Random Splicing: is Emotional Expression Preserved?
AbstractWe discuss the influence of random splicing on the perception of emotional expression in speech signals. Random splicing is the randomized reconstruction of short audio snippets with the aim to obfuscate the speech contents. A part of the German parliament recordings has been random spliced and both versions – the original and the scrambled ones – manually labeled with respect to the arousal, valence and dominance dimensions. Additionally, we run a state-of-the-art transformer-based pre-trained emotional model on the data. We find sufficiently high correlation for the annotations and predictions of emotional dimensions between both sample versions to be confident that machine learners can be trained with random spliced data.
ConferenceICASSP 2023 – 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date04-10 June 2023
LocationRhodes Island, Greece
Year of Publication2023

Key Facts

  • Project Coordinator: Dr. Sotiris Ioannidis
  • Institution: Foundation for Research and Technology Hellas (FORTH)
  • E-mail: 
  • Start: 01.01.2021
  • Duration: 36 months
  • Participating Organisations: 17
  • Number of countries: 12

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This project has received funding from the European Union’s Horizon 2020 Research and Innovation program under grant agreement No 957337. The website reflects only the view of the author(s) and the Commission is not responsible for any use that may be made of the information it contains.