`vad_auditok` model guide¶

Overview¶

vad_auditok is a VoiceHub voice activity detection integration. This page is generated from the model registry and its executable data and training contracts, so the documented support stays aligned with code.

Quickstart¶

python -m pip install voicehub

Install VoiceHub and the provider extra shown above.
Choose a checkpoint that matches this integration.
Place a supported recording at speech.wav.
Run detection and tune the threshold against labeled validation audio.

from voicehub import AutoModelForVoiceActivityDetection

model = AutoModelForVoiceActivityDetection.from_pretrained(
    'auditok-energy-vad',
    model_type='vad_auditok',
    device="cpu",
    lazy_load=True,
)
output = model.detect("speech.wav", threshold=0.5)
for segment in output.segments:
    print(segment.start, segment.end, segment.score)

Use only authorized recordings for reference voice, transcription, detection, or evaluation. The example selects a concrete device; verify checkpoint-specific hardware needs and pin an immutable revision before production use.

Supported tasks and capabilities¶

Property	Value
Task	Voice activity detection
Architecture	`energy-vad`
Runtime	`VoiceHub-native`
Capabilities	`voice-activity-detection`, `energy-based`, `adaptive-threshold`, `algorithmic`, `voicehub-native`
Reusable components	—

Data contract¶

Property	Value
Label boundary	No verified training dataset contract
Required training inputs	—

Use authorized audio and preserve annotation provenance. Follow the ASR and VAD data workflow for supported audio forms, timestamp labels, frame targets, leakage-safe splits, and evaluation.

Checkpoints, provenance, and license¶

Property	Value
Default checkpoint	`auditok-energy-vad`
Checkpoint status	Registry default; pin an immutable revision for production and reproducible evidence
Implementation	`voicehub.models.vad_auditok.modeling_vad_auditok.AuditokVADForVoiceActivityDetection`
Configuration	`voicehub.models.vad_auditok.configuration_vad_auditok.AuditokVADConfig`
Source provenance	No integration-specific bundled `SOURCE.json` is declared for this registry entry.
License	Checkpoint-specific

No VoiceHub-specific license override is registered. Verify the checkpoint and upstream source terms before use.

The default checkpoint identifies the expected family, not every compatible variant. Confirm the selected checkpoint's revision, access terms, provenance, and license before downloading or redistributing it.

Optimization and training support¶

All public optimizations enter this model through the shared BaseSpeechModel lifecycle. Use available_optimization_passes() to discover the public pass registry, then apply, inspect, serialize, or restore a plan through the common model API. Application remains fail-closed when the active runtime or hardware cannot satisfy a pass.

Training contract¶

Property	Value
Support	`inference-only`
Family	`upstream-native`
Recipe	`single-phase`
Default phase	`default`
Training checkpoint	`auditok-energy-vad`
Native training graph	`no`

Phase	Kind	Components	Required inputs	Loss keys
`default`	objective	—	—	`loss`, `total_loss`

This integration is intentionally inference-only. VoiceHub has no verified gradient-bearing graph, loss, and reloadable training artifact for it. Do not attach a generic loss to inference output. Choose a trainable model from the training matrix, or contribute a tested training adapter and data contract.

Public API¶

Purpose	Public object
Discover	`get_model_spec('vad_auditok')`
Load and run	`AutoModelForVoiceActivityDetection`
Configure	`AuditokVADConfig`
Model implementation	`AuditokVADForVoiceActivityDetection`
Normalized output	`VADOutput`
Training contract	`get_training_spec('vad_auditok')`
Optimization lifecycle	`available_optimization_passes`, `apply_optimization_plan`, `optimization_manifest`, `restore_optimization_plan`

vad_auditok model guide¶