VoiceActivityDetection.py

__author__ = 'Varun Nayyar'
__doc__ = \
    """
    This file is to be modified by users to provide their own Voice Activity Detection (VAD) functions.
    I.e. not all frames will have speech present and it is common to remove these frames in many situations

    These functions can be used in most base functions by passing VAD = myVADfunction where
    myVADfunction follows the template provided.
    """
import numpy as np

def templateVAD(frames, sig):
    """
    :param frames: numpy array of [NumFrames][SamplesPerFrame] of all the speech frames
    :param sig: The entire signal [signLen]
    :return: the subset of frames where there is voiced activity detected
    """
    raise NotImplementedError


def simpleVAD(frames, sig, threshold=0.01):
    """
    :param frames: numpy array of [NumFrames][SamplesPerFrame] of all the speech frames
    :param sig: The entire signal [signLen]
    :param threshold: above what level of average power must the frame be to be considered to have activity
    :return: the subset of frames where there is voiced activity detected

    Note that the variance of frame/signal represents the average power of the frame/signal
    so this is a power threshold activity detector applied along the frames
    """


    frameVars = np.var(frames, 1)
    reducedFrames = frames[np.where(frameVars > sig.var() * threshold)]
    return reducedFrames