pliers.extractors.AudiosetLabelExtractor

class pliers.extractors.AudiosetLabelExtractor(hop_size=0.1, top_n=None, labels=None, weights_path=None, **yamnet_kwargs)[source]

Bases: AudioExtractor

Extract probability of 521 audio event classes based on AudioSet corpus using a YAMNet architecture. Code available at: https://github.com/tensorflow/models/tree/master/research/audioset/yamnet

Args: hop_size (float): size of the audio segment (in seconds) on which label

extraction is performed.

top_n (int): specifies how many of the highest label probabilities are

returned. If None, all labels (or those passed to the labels argument) are returned. Top_n and labels are mutually exclusive.

labels (list): specifies subset of labels for which probabilities

are to be returned. If None, all labels (or top_n) are returned. The full list of labels is available in the audioset/yamnet repository (see yamnet_class_map.csv).

weights_path (optional): full path to model weights file. If not provided,

weights from pretrained YAMNet module are used.

yamnet_kwargs (optional): Optional named arguments that modify input

parameters for the model (see params.py file in yamnet repository)

__init__(hop_size=0.1, top_n=None, labels=None, weights_path=None, **yamnet_kwargs)[source]
transform(stim, *args, **kwargs)

Executes the transformation on the passed stim(s).

Parameters

  • stims (str, Stim, list) –

    One or more stimuli to process. Must be one of:

    • A string giving the path to a file that can be read in as a Stim (e.g., a .txt file, .jpg image, etc.)

    • A Stim instance of any type.

    • An iterable of stims, where each element is either a string or a Stim.

  • validation (str) –

    String specifying how validation errors should be handled. Must be one of:

    • ’strict’: Raise an exception on any validation error

    • ’warn’: Issue a warning for all validation errors

    • ’loose’: Silently ignore all validation errors

  • args – Optional positional arguments to pass onto the internal _transform call.

  • kwargs – Optional positional arguments to pass onto the internal _transform call.