Long-term Conversation Analysis: Exploring Utility and Privacy
Konferenz: Speech Communication - 15th ITG Conference
20.09.2023-22.09.2023 in Aachen
doi:10.30420/456164004
Tagungsband: ITG-Fb. 312: Speech Communication
Seiten: 5Sprache: EnglischTyp: PDF
Autoren:
Nespoli, Francesco (Microsoft, London, UK & Dept. Electrical and Electronic Engineering, Imperial College London, UK)
Pohlhausen, Jule (Institute of Hearing Technology and Audiology, Jade University of Applied Sciences, Oldenburg, Germany)
Naylor, Patrick A. (Dept. Electrical and Electronic Engineering, Imperial College London, UK)
Bitzer, Joerg (Institute of Hearing Technology and Audiology, Jade University of Applied Sciences, Oldenburg, Germany & Fraunhofer IDMT Dept. HSA, Oldenburg, Germany)
Inhalt:
The analysis of conversations recorded in everyday life requires privacy protection. In this contribution, we explore a privacy-preserving feature extraction method based on input feature dimension reduction, spectral smoothing and the low-cost speaker anonymization technique based on McAdams coefficient. We assess the utility of the feature extraction methods with a voice activity detection and a speaker diarization system, while privacy protection is determined with a speech recognition and a speaker verification model. We show that the combination of the McAdams coefficient and spectral smoothing maintains the utility while improving privacy.