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This page contains details about the models compatible with the current version of the SDK.
All models are language-agnostic and can be used for any language, as they operate on the acoustic properties of the audio signal rather than processing its linguistic content.All models can also be used with any sample rate using our SDK. You can learn more about that here.

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Quail

Speech Enhancement for Voice AI Quail is a general-purpose speech enhancement model. It works in any setting, single- or multi-speaker and near- or far-field, suppressing background noise while preserving all audible speech. Unlike Quail Voice Focus, it does not single out a primary speaker, making it the right choice when every voice should be kept, such as speakerphone setups, meeting rooms, or situations with multiple participants spread across a space.
  • ID: quail-l-16khz
  • File size: 35 MB
  • Window length: 10 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 160
  • Minimal algorithmic delay: 30 ms
  • ID: quail-l-8khz
  • File size: 33.4 MB
  • Window length: 10 ms
  • Native sample rate: 8 kHz
  • Native num frames: 80
  • Minimal algorithmic delay: 30 ms
  • ID: quail-s-16khz
  • File size: 8.88 MB
  • Window length: 10 ms
  • Native sample rate: 16 kHz
  • Native num frames: 160
  • Minimal algorithmic delay: 30 ms
  • ID: quail-s-8khz
  • File size: 8.43 MB
  • Window length: 10 ms
  • Native sample rate: 8 kHz
  • Native num frames: 80
  • Minimal algorithmic delay: 30 ms
Model files available for download here.

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Quail Voice Focus

Primary Speaker Isolation for Voice AI Quail Voice Focus isolates the primary speaker. It is designed for settings where one or more speakers may be present but the application targets a single speaker, suppressing interfering speech, residual echo, and background noise.
  • ID: quail-vf-2.2-l-16khz
  • File size: 20 MB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
  • ID: quail-vf-2.2-s-16khz
  • File size: 5 MB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
  • ID: quail-vf-2.1-l-16khz
  • File size: 20 MB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
  • ID: quail-vf-2.1-s-16khz
  • File size: 5 MB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
Model files available for download here.

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Quail VAD

Noise-robust Voice Activity Detection Quail VAD is a general-purpose and noise-robust voice activity detection model. It detects all audible speech in any setting, single- or multi-speaker and near- or far-field, and is robust to background noise. Unlike Quail Voice Focus VAD, it does not single out a primary speaker, making it the right choice when activity from any speaker should be detected.
  • ID: quail-vad-2.0-xxs-16khz
  • File size: 630 kB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
Model files available for download here.

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Quail Voice Focus VAD

Primary Speaker Voice Activity Detection for Voice AI Quail Voice Focus VAD detects voice activity for the primary speaker only. It is designed for settings where one or more speakers may be present but the application targets a single speaker, ignoring interfering speech and background noise so the VAD fires only on the target speaker.
  • ID: quail-vf-vad-2.0-s-16khz
  • File size: 630 kB
  • Window length: 15 ms
  • Optimal sample rate: 16 kHz
  • Optimal num frames: 240
  • Minimal algorithmic delay: 30 ms
Model files available for download here.

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Tyto

Audio Insight for Voice AI Tyto is an audio intelligence model that predicts whether an audio signal is likely to cause failures in the downstream models that consume it (VAD, turn-taking, STT and speech-to-speech).
  • ID: tyto-l-16khz
  • File size: 19.8 MB
  • Window length: 5 s
  • Native sample rate: 16 kHz
Model files available for download here.

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Rook

Speech Enhancement for Human Intelligibility Rook reduces background noise and reverberation while preserving speech naturalness and intelligibility for human perception.
  • ID: rook-l-48khz
  • File size: 35.1 MB
  • Window length: 10 ms
  • Native sample rate: 48 kHz
  • Native num frames: 480
  • Minimal algorithmic delay: 30 ms
  • ID: rook-l-16khz
  • File size: 35 MB
  • Window length: 10 ms
  • Native sample rate: 16 kHz
  • Native num frames: 160
  • Minimal algorithmic delay: 30 ms
  • ID: rook-l-8khz
  • File size: 33.4 MB
  • Window length: 10 ms
  • Native sample rate: 8 kHz
  • Native num frames: 80
  • Minimal algorithmic delay: 30 ms
  • ID: rook-s-48khz
  • File size: 8.96 MB
  • Window length: 10 ms
  • Native sample rate: 48 kHz
  • Native num frames: 480
  • Minimal algorithmic delay: 30 ms
  • ID: rook-s-16khz
  • File size: 8.88 MB
  • Window length: 10 ms
  • Native sample rate: 16 kHz
  • Native num frames: 160
  • Minimal algorithmic delay: 30 ms
  • ID: rook-s-8khz
  • File size: 8.43 MB
  • Window length: 10 ms
  • Native sample rate: 8 kHz
  • Native num frames: 80
  • Minimal algorithmic delay: 30 ms
Model files available for download here.

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Using models with non-native sample rates

Our models are trained for specific sample rates (8 kHz, 16 kHz, and 48 kHz). However, the ai-coustics SDK allows you to use any model with audio at non-native sample rates by internally resampling the input. The model always processes the audio at its native sample rate. You can choose any sample rate between 8 kHz and 192 kHz when calling the processor’s initialize function in the SDK, regardless of the model being used. Higher-than-native sample rate (e.g. 48 kHz audio with a 16 kHz model): In this case, the SDK cuts away the frequency content above the model’s native Nyquist frequency (everything above half the sample rate) before feeding it to the model. The SDK output is then upsampled back to the original sample rate. The mixback (enhancement_level) stays at the higher sample rate, so the output will contain the full frequency range of the original audio, but the model’s enhancement will only be applied to the frequencies within the model’s native Nyquist frequency. Lower-than-native sample rate (e.g. 8 kHz audio with a 16 kHz model): When the input audio sample rate is lower than the model’s native sample rate, compute resources are effectively “wasted” processing higher frequencies where no signal is contained (the model is just processing zeros). Therefore, if there is a model available matching your audio’s sample rate, we recommend using that model to avoid unnecessary compute and ensure optimal performance. In both cases, CPU consumption is only marginally affected by the input sample rate.
Learn more about performance here.

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Compatibility

All models can be used in any of our available integrations, including all of our SDK language bindings and Pipecat filter. The LiveKit plugin has a limited selection of models available. For more information, see here. For more information about model compatibility with our different integrations, see the compatibility matrix.