PraatIntensityEnvelope

Defined in: voxatlas.features.acoustic.envelope.praat_intensity

class voxatlas.features.acoustic.envelope.praat_intensity.PraatIntensityEnvelope

Bases: BaseExtractor

Extract the acoustic.envelope.praat_intensity feature within the VoxAtlas pipeline.

Computes a smoothed, frame-aligned intensity-like contour intended to serve as a lightweight proxy for Praat-style intensity tracking.

Algorithm

The implementation mirrors the code path.

1. RMS amplitude The waveform is framed and converted to RMS values \(r_t\).

2. Smoothing The RMS contour is smoothed with a moving-average window of length smoothing frames.

Notes

This extractor does not attempt to reproduce Praat’s full intensity computation (e.g., frequency weighting and dB scaling). It provides a consistent, frame-aligned contour suitable for downstream transforms.

name

Registry key for this extractor ("acoustic.envelope.praat_intensity").

Type:

str

input_units

Required input unit level. None means this extractor operates directly on waveform audio.

Type:

str | None

output_units

Output alignment unit ("frame").

Type:

str | None

dependencies

Upstream features required before execution. Empty for this extractor.

Type:

list[str]

default_config

Default runtime parameters: frame_length=0.025, frame_step=0.01, peak_threshold=0.1, smoothing=5.

Type:

dict

References

Boersma, P. (2001). Praat, a system for doing phonetics by computer. *Glot International, 5*(9/10), 341–345.

Examples

>>> import numpy as np
>>> from voxatlas.audio.audio import Audio
>>> from voxatlas.features.acoustic.envelope.praat_intensity import PraatIntensityEnvelope
>>> from voxatlas.features.feature_input import FeatureInput
>>> audio = Audio(waveform=np.zeros(1600, dtype=np.float32), sample_rate=16000)
>>> feature_input = FeatureInput(audio=audio, units=None, context={})
>>> params = PraatIntensityEnvelope.default_config.copy()
>>> out = PraatIntensityEnvelope().compute(feature_input, params)
>>> out.unit
'frame'

name: str = 'acoustic.envelope.praat_intensity'

input_units: str | None = None

output_units: str | None = 'frame'

dependencies: list[str] = []

default_config: dict = {'frame_length': 0.025, 'frame_step': 0.01, 'peak_threshold': 0.1, 'smoothing': 5}

compute(feature_input, params)

Compute the extractor output for a single pipeline invocation.

This method is the reusable execution entry point for the extractor. It receives the standard FeatureInput bundle, applies the configured algorithm, and returns feature values aligned to the extractor output units for storage in the pipeline feature store.

Parameters:

• feature_input (object) – Structured extractor input bundling audio, hierarchical units, and execution context for this feature computation.

• params (object) – Resolved feature configuration for this invocation. Keys are feature-specific and merged from defaults and pipeline settings.

Returns:

Structured output aligned to the frame unit level when applicable.

Return type:

FeatureOutput

Examples

>>> import numpy as np
>>> from voxatlas.audio.audio import Audio
>>> from voxatlas.features.acoustic.envelope.praat_intensity import PraatIntensityEnvelope
>>> from voxatlas.features.feature_input import FeatureInput
>>> audio = Audio(waveform=np.zeros(1600, dtype=np.float32), sample_rate=16000)
>>> feature_input = FeatureInput(audio=audio, units=None, context={})
>>> params = PraatIntensityEnvelope.default_config.copy()
>>> result = PraatIntensityEnvelope().compute(feature_input, params)
>>> result.values.shape[0] > 0
True