import numpy as np
from VuVoPy.data.containers.prepocessing import Preprocessed as pp
from VuVoPy.data.containers.sample import VoiceSample as vs
from VuVoPy.data.containers.segmentation import Segmented as sg
from VuVoPy.data.utils.vuvs_detection import Vuvs as vuvs
[docs]
def durmed(folder_path, winlen = 512, winover = 496 , wintype = 'hamm'):
"""
Calculate the median silence duration from a voice sample.
This function processes a voice sample from a given file path, segments it
using specified window parameters, and calculates the median duration of
silence segments.
Args:
folder_path (str): The file path to the voice sample in WAV format.
winlen (int, optional): The length of the analysis window. Default is 512.
winover (int, optional): The overlap between consecutive windows. Default is 496.
wintype (str, optional): The type of window to apply (e.g., 'hamm' for Hamming). Default is 'hamm'.
Returns:
float: The median duration of silence segments in the voice sample.
"""
preprocessed_sample = pp.from_voice_sample(vs.from_wav(folder_path))
segment = sg.from_voice_sample(preprocessed_sample, winlen, wintype, winover)
fs = segment.get_sampling_rate()
labels = vuvs(segment, fs=fs, winlen =segment.get_window_length(), winover = segment.get_window_overlap(), wintype=segment.get_window_type(), smoothing_window=5)
return np.median(labels.get_silence_durations())