Toward Complete Speaker Anonymization: a Streaming Cascaded System for Voice Privacy and PII Removal

We present a cascade streaming voice privacy system, consisting of ASR, NLP, and TTS modules. By leveraging recent improvements in all three aspects of speech and language processing, we show that such a system is capable of achieving a result comparable to state-of-the-art offline voice privacy systems, while providing controllable capabilities of content protection beyond voice. With an estimated utterance-onset end-to-end latency of 717 ms, the presented system preserves speech content with 11% WER on Librispeech, while detecting PII with a 69% SLU F1 score and achieving up to 47.66% EER against a semi-informed attacker.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39754
Primary Topic
Speech Recognition and Synthesis
Type
preprint
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preprint

Toward Complete Speaker Anonymization: a Streaming Cascaded System for Voice Privacy and PII Removal

Stanisław Kacprzak, Thomas Thebaud, Najim Dehak
arXiv (Cornell University)
Speech Recognition and Synthesis
preprint

Toward Complete Speaker Anonymization: a Streaming Cascaded System for Voice Privacy and PII Removal

Stanisław Kacprzak, Thomas Thebaud, Najim Dehak
preprint en

Abstract

We present a cascade streaming voice privacy system, consisting of ASR, NLP, and TTS modules. By leveraging recent improvements in all three aspects of speech and language processing, we show that such a system is capable of achieving a result comparable to state-of-the-art offline voice privacy systems, while providing controllable capabilities of content protection beyond voice. With an estimated utterance-onset end-to-end latency of 717 ms, the presented system preserves speech content with 11% WER on Librispeech, while detecting PII with a 69% SLU F1 score and achieving up to 47.66% EER against a semi-informed attacker.

arXiv (Cornell University)
Speech Recognition and Synthesis
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