Using Keyword Spotting and Replacement for Speech Anonymization

Privacy protection issue introduces numerous challenges in the multimedia processing domain. In this paper, we propose an anonymization framework for audio clinical data. The HMM based keyword recognition technique is used to locate the predefined sensitive keywords, which are identified by the users or patients in advance. These keywords will then be substituted by the synthesized nominal words of the similar nature and voice characteristics. The ultimate goal is to protect the privacy information as much as possible, while trying to preserve the speech properties, especially the disease-related symptoms, such as the loudness, the rhythm, the emotion, etc. A preliminary system is presented to demonstrate the usage of the process.