Skip to main content
Quail Voice Focus targets one primary speaker while suppressing competing speech, background noise and residual echo. Use it when a voice agent should follow one participant, rather than transcribe every voice in a room. Voice Focus uses recent audio context to select the primary speaker. At the beginning of a stream, suppression can be weaker while that context builds. Test startup with short utterances and quiet speakers; there is no fixed warm-up duration guaranteed by this guide. Keep processing continuous across adjacent frames so the model can retain context. Primary-speaker selection can change when another speaker becomes more prominent, such as when someone moves closer to the microphone. It is not a persistent identity lock. If your application requires identity verification or a fixed enrolled speaker, model selection alone does not establish that behavior.

​
Choose a variant

For core SDK 0.24.0, start with quail-vf-2.2-l-16khz or compare the smaller quail-vf-2.2-s-16khz on your target hardware. Both have a native rate of 16 kHz and an optimal native block size of 240 samples. See the model reference for acquisition and compatibility.

​
Check speech retention

Compare original and enhanced recordings using your speech-to-text (STT) provider. Include quiet target speech, overlapping speech, speaker changes and the first seconds after a reset. Measure target-word deletions as well as background-word insertions; stronger suppression can remove speech you intended to retain. For dedicated ai-coustics voice activity detection (VAD), use the original input audio. VAD Voice Focus targets primary-speaker activity when only the target speaker should drive speech activity. A third-party VAD may behave differently on enhanced audio; evaluate its speech boundaries and added delay separately. Follow Voice Focus tuning and the SDK quickstart for the next step.