New Challenges for Content Privacy in Speech and Audio
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Abstract (arXiv)
Privacy in speech and audio has many facets. A particularly under-developed area of privacy in this domain involves consideration for information related to content and context. Speech content can include words and their meaning or even stylistic markers, pathological speech, intonation patterns, or emotion. More generally, audio captured in-the-wild may contain background speech or reveal contextual information such as markers of location, room characteristics, paralinguistic sounds, or other audible events. Audio recording devices and speech technologies are becoming increasingly commonplace in everyday life. At the same time, commercialised speech and audio technologies do not provide consumers with a range of privacy choices. Even where privacy is regulated or protected by law, technical solutions to privacy assurance and enforcement fall short. This position paper introduces three important and timely research challenges for content privacy in speech and audio. We highlight current gaps and opportunities, and identify focus areas, that could have significant implications for developing ethical and safer speech technologies.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Jan 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2026The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymizationcited by 8
- 2024Exploratory Evaluation of Speech Content Maskingcited by 3
- 2025Content Anonymization for Privacy in Long-form Audiocited by 3
- 2025Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attackscited by 0
- 2026The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization17 Jan 2026
- 2025Content Anonymization for Privacy in Long-form Audio14 Oct 2025
- 2025Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks30 Jan 2025
- 2024Exploratory Evaluation of Speech Content Masking8 Jan 2024