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Privacy preserving speech analysis using emotion filtering at the edge: poster abstract

Published: 10 November 2019 Publication History

Abstract

Voice controlled devices and services are commonplace in consumer IoT. Cloud-based analysis services extract information from voice input using speech recognition techniques. Services providers can build detailed profiles of users' demographics, preferences and emotional states, etc., and may therefore significantly compromise privacy. To address this problem, a privacy-preserving intermediate layer between users and cloud services is proposed to sanitize voice input directly at edge devices by generating neutralized signals for forwarding. We show that a trained model, based on CycleGAN and deployed on a Raspberry Pi, enables identification and removal of sensitive emotional state information by ~91%, with minimal losses to speech recognition accuracy.

References

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2019. Emotion-Classification-Ravdess. https://github.com/marcogdepinto/Emotion-Classification-Ravdess
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Affectiva. [n. d.]. Emotion AI. https://www.affectiva.com/emotion-ai-overview/
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Ranya Aloufi, Hamed Haddadi, and David Boyle. 2019. Emotion Filtering at the Edge. (Sep 2019). arXiv:1909.08500
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Ranya Aloufi, Hamed Haddadi, and David Boyle. 2019. Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants. arXiv:1908.03632
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IBM. 2019. IBM Watson Speech to Text. https://speech-to-text-demo.ng.bluemix.net
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Huafeng Jin and Shuo Wang. 2018. Voice-based determination of physical and emotional characteristics of users.
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Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka, and Nobukatsu Hojo. 2019. CycleGAN-VC2: Improved CycleGAN-based Non-parallel Voice Conversion.
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Steven R Livingstone and Frank A Russo. 2018. The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. (2018).
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Masanori Morise, Fumiya Yokomori, and Kenji Ozawa. 2016. WORLD: a vocoder-based high-quality speech synthesis system for real-time applications. (2016).
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Andreas Nautsch, Abelino Jiménez, Amos Treiber, Jascha Kolberg, Catherine Jasserand, Els Kindt, Héctor Delgado, Massimiliano Todisco, Mohamed Amine Hmani, Aymen Mtibaa, et al. 2019. Preserving Privacy in Speaker and Speech Characterisation. (2019).
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Scott R Peppet. 2014. Regulating the internet of things: first steps toward managing discrimination, privacy, security and consent. (2014).
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Weidi Xie, Arsha Nagrani, Joon Son Chung, and Andrew Zisserman. 2019. Utterance-level Aggregation For Speaker Recognition In The Wild. (2019).
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Cited By

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  • (2022)Privacy-Preserving Speech RecognitionEncyclopedia of Machine Learning and Data Science10.1007/978-1-4899-7502-7_984-1(1-6)Online publication date: 8-Mar-2022
  • (2021)Anti Leakage: Protecting Privacy Hidden in Our Speech2021 7th International Conference on Big Data Computing and Communications (BigCom)10.1109/BigCom53800.2021.00011(114-120)Online publication date: Aug-2021
  • (2020)When Speakers Are All Ears: Characterizing Misactivations of IoT Smart SpeakersProceedings on Privacy Enhancing Technologies10.2478/popets-2020-00722020:4(255-276)Online publication date: 17-Aug-2020
  • Show More Cited By

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  1. Privacy preserving speech analysis using emotion filtering at the edge: poster abstract

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      cover image ACM Conferences
      SenSys '19: Proceedings of the 17th Conference on Embedded Networked Sensor Systems
      November 2019
      472 pages
      ISBN:9781450369503
      DOI:10.1145/3356250
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 10 November 2019

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      Author Tags

      1. internet of things (IoT)
      2. machine learning
      3. speech analysis
      4. voice privacy
      5. voice synthesis

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      Cited By

      View all
      • (2022)Privacy-Preserving Speech RecognitionEncyclopedia of Machine Learning and Data Science10.1007/978-1-4899-7502-7_984-1(1-6)Online publication date: 8-Mar-2022
      • (2021)Anti Leakage: Protecting Privacy Hidden in Our Speech2021 7th International Conference on Big Data Computing and Communications (BigCom)10.1109/BigCom53800.2021.00011(114-120)Online publication date: Aug-2021
      • (2020)When Speakers Are All Ears: Characterizing Misactivations of IoT Smart SpeakersProceedings on Privacy Enhancing Technologies10.2478/popets-2020-00722020:4(255-276)Online publication date: 17-Aug-2020
      • (2020)Synchronized Preprocessing of Sensor Data2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377900(3522-3531)Online publication date: 10-Dec-2020

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