Privacy Preserving Speech Processing

نویسندگان

  • Manas A. Pathak
  • Bhiksha Raj
  • Shantanu Rane
  • Paris Smaragdis
چکیده

Speech is one of the most private forms of communication. People do not like to be eavesdropped on. They will frequently even object to being recorded; in fact in many places it is illegal to record people speaking in public, even when it is acceptable to capture their images on video [1]. Yet, when a person uses a speech-based service such as a voice authentication system or a speech recognition service, they must grant the service complete access to their voice recordings. This exposes the user to abuse, with security, privacy and economic implications. For instance, the service could extract information such as gender, ethnicity, and even the emotional state of the user from the recording factors not intended to be exposed by the user and use them for undesired purposes. The recordings may be edited to create fake recordings that the user never spoke, or to impersonate them for other services. Even derivatives from the voice are risky to expose. E.g. a voice-authentication service could make unauthorized use of the models or voice prints it has for users to try to identify their presence in other media such as YouTube. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c © Mitsubishi Electric Research Laboratories, Inc., 2013 201 Broadway, Cambridge, Massachusetts 02139

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Privacy Preserving Techniques for Speech Processing

Speech is perhaps the most private form of personal communication but current speech processing techniques are not designed to preserve the privacy of the speaker and require complete access to the speech recording. We propose to develop techniques for speech processing which do preserve privacy. While our proposed methods can be applied to a variety of speech processing problems and also gener...

متن کامل

A centralized privacy-preserving framework for online social networks

There are some critical privacy concerns in the current online social networks (OSNs). Users' information is disclosed to different entities that they were not supposed to access. Furthermore, the notion of friendship is inadequate in OSNs since the degree of social relationships between users dynamically changes over the time. Additionally, users may define similar privacy settings for their f...

متن کامل

Towards Privacy-Preserving Speech Data Publishing

Privacy-preserving data publishing has been a heated research topic in the last decade. Numerous ingenious attacks on users’ privacy and defensive measures have been proposed for the sharing of various data, varying from relational data, social network data, spatiotemporal data, to images and videos. Speech data publishing, however, is still untouched in the literature. To fill this gap, we stu...

متن کامل

Privacy Preserving Speaker Verification Using Adapted GMMs

In this paper we present an adapted UBM-GMM based privacy preserving speaker verification (PPSV) system, where the system is not able to observe the speech data provided by the user and the user does not observe the models trained by the system. These privacy criteria are important in order to prevent an adversary having unauthorized access to the user’s client device from impersonating a user ...

متن کامل

Finding the state sequence maximizing P(O; I|λ) on distributed HMMs with Privacy

Hidden Markov models (HMMs) are widely used by many applications for forecasting purposes. They are increasingly becoming popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, signal processing, and so on. Given an HMM, an application of HMMs is to choose a state sequence so that the joint probability of an observation sequence and a state sequ...

متن کامل

A Lightweight Privacy-preserving Authenticated Key Exchange Scheme for Smart Grid Communications

Smart grid concept is introduced to modify the power grid by utilizing new information and communication technology. Smart grid needs live power consumption monitoring to provide required services and for this issue, bi-directional communication is essential. Security and privacy are the most important requirements that should be provided in the communication. Because of the complex design of s...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013