*Hi Everyone,Pleased to present CFP for Interspeech 2021 Special Session on Privacy-preserving Machine Learning for Audio & Speech Processing (PPML)https://sites.google.com/view/ppmlforaudio/home <https://sites.google.com/view/ppmlforaudio/home>Interspeech PPML special session focuses on privacy-preserving machine learning (PPML) techniques in speech, language and audio processing, including centralized, distributed and on-device processing approaches. Novel contributions and overviews on the theory and applications of PPML in speech, language and audio are invited. We encourage submissions related to ethical and regulatory aspects of PPML in this context. Sending speech, language or audio data to a cloud server exposes private information. One approach called anonymization is to preprocess the data so as to hide information which could identify the user by disentangling it from other useful attributes. PPML is a different approach, which solves this problem by moving computation near the clients. In addition to privacy, PPML improves the user experience due to increased accuracy and lower latency from on-device processing. Tech companies have recently reported leveraging PPML approaches such as Federated learning for improving their user experiences while preserving user’s privacy.Relevant topics include but are not limited to:● Theory, implementation, and applications of statistical notions of privacy such as Differential Privacy● Federated or decentralized learning for speech, language and audio processing.● Privacy-preserving representation learning for audio and speech tasks, including Adversarial approaches.● On-device training, adaptation, and inference of audio ML models● Hardware optimization, sparsity, quantization, power savings and algorithmic trade-offs for on-device training and inference● Generation and usage of synthetic speech, text, and audio for training ML models for Speech Recognition, Speaker Recognition, Keyword Spotting, etc.● Secure multi-party computation, homomorphic encryption, secure enclaves, privacy attacks and mitigation approaches for PPML in audio and speech processing.● Machine learning on encrypted speech, language, and audio data● Tools, processes and benchmarks for PPML in speech, language, and audio processingKeynote Talk: Prof. Isabel Trancoso <https://www.hlt.inesc-id.pt/w/Isabel_Trancoso>, Instituto Superior Técnico (IST, Univ. Lisbon)Session Format: This session will be organized into two phases. In Phase I, authors will give 2-minute lightning talks for their papers which will be followed by a keynote talk. In Phase II, papers will be presented in the form of posters.Paper Submission: Papers for PPML Special Session have to be submitted following the same schedule and procedure as regular papers of INTERSPEECH 2021. The submitted papers will undergo the same review process by anonymous and independent reviewers. - Submission url: https://www.softconf.com/l/interspeech2021/user/ <https://www.softconf.com/l/interspeech2021/user/>To submit papers to this session, please choose "14.16 Privacy-preserving Machine Learning for Audio, Speech and Language Processing" in 14 Special Sessions listed in INTERSPEECH 2021 paper submission system. - Submission deadline: same as INTERSPEECH submission deadline (March 26, 2021)- Notification of acceptance: June 2, 2021- Camera Ready: June 15, 2021Organizers:Harishchandra Dubey (Microsoft)Amin Fazel (Amazon)Mirco Ravanelli (MILA , Université de Montréal)Emmanuel Vincent (Inria) * -Best, Hari
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