Speech Segregation based on Pitch Track Correction and Music-Speech Classification

Monaural speech segregation based on pitch track correction using an ensemble kalman filter

We propose a novel method of pitch track correction that uses an ensemble Kalman filter to improve the performance of monaural speech segregation. The proposed method considers all reliable pitch streaks for pitch track correction, whereas the conventional segregation approach relies on only the longest streak in a given speech stream. In addition, unreliable pitch streaks are corrected with an...

Monaural Speech Segregation Based on Pitch

Introduction The goal of the proposed algorithm is to separate speech signals in monaural recordings even in very adverse conditions when significant background noise and additional speakers are present at the same time. Particularly we try to decide for each time frequency region which of the different sound sources dominates and then build for each sound source a binary mask which is one at t...

Pitch-based monaural segregation of reverberant speech.

In everyday listening, both background noise and reverberation degrade the speech signal. Psychoacoustic evidence suggests that human speech perception under reverberant conditions relies mostly on monaural processing. While speech segregation based on periodicity has achieved considerable progress in handling additive noise, little research in monaural segregation has been devoted to reverbera...

Pitch-Based Segregation of Reverberant Speech

Speech Segregation based on Binary Classification

Speech segregation is a fundamental challenge in speech and audio processing. This AFOSR project aimed to develop a speech segregation system that can potentially improve speech intelligibility in noise for human listeners. Motivated by the perceptual principles of auditory scene analysis and the speech intelligibility studies of ideal time-frequency masking, the project sought to develop a cla...