A de Cheveigne

AS Bregman

D Talkin

DL Wang

G Hu

GJ Brown

J Barker

J Le Roux

J Tabrikian

JJ Sroka

L Atlas

M Buchler

M Wu

MH Radfar

MP Cooke

Q Li

R Drullman

RP Lippmann

S Dubnov

SM Schimmel

TW Lee

X Huang

Y Shao

EURASIP Journal on Advances in Signal Processing

English

Abstract
          Computational Auditory Scene Analysis (CASA) has been the focus in recent literature for speech separation from monaural mixtures. The performance of current CASA systems on voiced speech separation strictly depends on the robustness of the algorithm used for pitch frequency estimation. We propose a new system that estimates pitch (frequency) range of a target utterance and separates voiced portions of target speech. The algorithm, first, estimates the pitch range of target speech in each frame of data in the modulation frequency domain, and then, uses the estimated pitch range for segregating the target speech. The method of pitch range estimation is based on an onset and offset algorithm. Speech separation is performed by filtering the mixture signal with a mask extracted from the modulation spectrogram. A systematic evaluation shows that the proposed system extracts the majority of target speech signal with minimal interference and outperforms previous systems in both pitch extraction and voiced speech separation.</jats:p

Azar Mahmoodzadeh

Hamid Reza Abutalebi

Hamid Soltanian-Zadeh

Hamid Sheikhzadeh

Crossref

Single channel speech separation in modulation frequency domain based on a novel pitch range estimation method

https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/1687-6180-2012-67?site=asp-eurasipjournals.springeropen.com

Single channel speech separation in modulation frequency domain based on a novel pitch range estimation method

Abstract

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