SDLGASMar 8, 2022

Digital Speech Algorithms for Speaker De-Identification

arXiv:2203.03932v13 citationsh-index: 3
Originality Synthesis-oriented
AI Analysis

This work addresses speaker de-identification in multimedia for privacy protection, but it is incremental as it focuses on evaluating existing algorithms rather than introducing new methods.

The study tested four voice modification algorithms on a speech gender recognizer to determine the pitch modification level needed for equal success and failure probabilities, assessing modification intensity, quality, and reversibility.

The present work is based on the COST Action IC1206 for De-identification in multimedia content. It was performed to test four algorithms of voice modifications on a speech gender recognizer to find the degree of modification of pitch when the speech recognizer have the probability of success equal to the probability of failure. The purpose of this analysis is to assess the intensity of the speech tone modification, the quality, the reversibility and not-reversibility of the changes made.

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