NDLI: Computationally efficient and noise robust DOA and pitch estimation

Content Provider	ACM Digital Library
Author	Jensen, Jesper Rindom Karimian-azari, Sam Christensen, Mads Græbøll
Copyright Year	2016
Abstract	Many natural signals, such as voiced speech and some musical instruments, are approximately periodic over short intervals. These signals are often described in mathematics by the sum of sinusoids (harmonics) with frequencies that are proportional to the fundamental frequency, or pitch. In sensor (microphone) array signal processing, the periodic signals are estimated from spatiotemporal samples regarding to the direction of arrival (DOA) of the signal of interest. In this paper, we consider the problem of pitch and DOA estimation of quasi-periodic audio signals. In reallife scenarios, recorded signals are often contaminated by different types of noise, which challenges the assumption of white Gaussian noise in most state-of-the-art methods. We establish filtering methods based on noise statistics to apply to nonparametric spectral and spatial parameter estimates of the harmonics. We design minimum variance solutions with distortionless constraints to estimate the pitch from the frequency estimates, and to estimate the DOA from multichannel phase estimates of the harmonics. Applying this filtering method as the sum of weighted frequency and DOA estimates of the harmonics, we also design a joint DOA and pitch estimator. In white Gaussian noise, we derive even more computationally efficient solutions which are designed using the narrowband power spectrum of the harmonics. Numerical results reveal the performance of the estimators in colored noise compared with the Cramér--Rao lower bound. Experiments on real-life signals indicate the applicability of the methods in practical low local signal-to-noise ratios.
Starting Page	1609
Ending Page	1621
Page Count	13
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	9
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-09-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Analytical signal Direction of arrival (DOA) estimation Harmonic signal model Minimum variance distortionless response (MVDR) Pitch estimation
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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