Streaming system protects voice privacy and removes personal info fast
Toward Complete Speaker Anonymization: a Streaming Cascaded System for Voice Privacy and PII Removal
Sound
Summary
This paper shows a new system that can protect your voice identity when speaking, by removing personal information in real time. The system combines speech recognition, language understanding, and voice synthesis in a sequence to keep your spoken content clear while hiding who you are and sensitive details. The authors demonstrate it works almost as well as slower offline systems but with much less delay. They also provide ways to control how much content or personal info gets protected.
What this means in practice
- •For voice assistant developers: Build voice assistants that remove personal info from spoken commands in real time to protect user privacy.$Commercial implications: Enables selling privacy-focused voice assistant software that anonymizes user speech and removes private details on the fly.
- •For call center operators: Integrate a streaming system to anonymize caller voices and redact personal info during live conversations to enhance data privacy.
Authors
Stanisław Kacprzak, Thomas Thebaud, Najim Dehak
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.