TY - GEN
T1 - Modeling Pseudo-Speaker Uncertainty in Voice Anonymization
AU - Chen, Liping
AU - Lee, Kong Aik
AU - Guo, Wu
AU - Ling, Zhen Hua
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/4/14
Y1 - 2024/4/14
N2 - Voice anonymization refers to the goal of suppressing personally identifiable voice attributes in speech. State-of-the-art models based on the voice conversion framework accomplish this goal by replacing the voice attributes of the speaker with those of a pseudo-speaker. This paper proposes to exploit the uncertainty estimate of pseudo-speaker in voice anonymization. For each target speaker, a pseudo-speaker distribution, characterized by a point estimate and its uncertainty, is estimated from a selected set of cohort speakers. Based on this distribution, a pseudo-speaker vector is sampled and used to replace the voice attributes in an anonymized speech. The efficacy of the proposed method was validated in the framework as provided by VoicePrivacy Challenge 2022. Audio samples can be found in https://voiceprivacy.github.io/pseudo-speaker-vector/.
AB - Voice anonymization refers to the goal of suppressing personally identifiable voice attributes in speech. State-of-the-art models based on the voice conversion framework accomplish this goal by replacing the voice attributes of the speaker with those of a pseudo-speaker. This paper proposes to exploit the uncertainty estimate of pseudo-speaker in voice anonymization. For each target speaker, a pseudo-speaker distribution, characterized by a point estimate and its uncertainty, is estimated from a selected set of cohort speakers. Based on this distribution, a pseudo-speaker vector is sampled and used to replace the voice attributes in an anonymized speech. The efficacy of the proposed method was validated in the framework as provided by VoicePrivacy Challenge 2022. Audio samples can be found in https://voiceprivacy.github.io/pseudo-speaker-vector/.
KW - pseudo-speaker distribution
KW - pseudo-speaker vector
KW - speaker uncertainty
KW - Voice anonymization
UR - http://www.scopus.com/inward/record.url?scp=85195393638&partnerID=8YFLogxK
U2 - 10.1109/ICASSP48485.2024.10446573
DO - 10.1109/ICASSP48485.2024.10446573
M3 - Conference article published in proceeding or book
AN - SCOPUS:85195393638
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 11601
EP - 11605
BT - 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024
Y2 - 14 April 2024 through 19 April 2024
ER -