VoxLock: Target-Speaker Extraction for Voice Agents Without an Enrollment Step

Arbaz Siddiqui

VoxLock: Target-Speaker Extraction for Voice Agents Without an Enrollment Step: 1 upvotes on Hugging Face Daily Papers, #23 of 29 papers on 2026-11-02. Day-by-day upvote history.

A voice agent's speech recognizer transcribes everyone near the microphone, including people other than the caller. I fine-tuned a public causal target-speaker extraction model (REAL-TSE, 27M parameters) on one GPU to work from a voice sample cut from the call itself, and released it as VoxLock. I score it by what a recognizer writes on real recordings. On Krisp's 265-recording benchmark it reaches 4.95% WER against 23.21% unprocessed and lets 9 background words into the transcript over 85 minutes of background-only speech. Its WER is not significantly different from Krisp's best filters and is significantly lower than the other commercial and open systems I tested. On 400 AMI meeting windows built and frozen before scoring, it cuts WER from 42.95% to 10.63%. The 8-bit model runs a live call on 77% of one CPU thread with 24 ms of algorithmic latency. Model, code and per-file scores are open.

Paper page on Hugging Face · arXiv

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