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New report available on pitch tracking

The following technical report is available via WWW:

"A Multipitch Tracking Algorithm for Noisy Speech"

Technical Report #25, Dec 2001

Department of Computer and Information Science
The Ohio State University

        Mingyang Wu, The Ohio State University
        DeLiang Wang, The Ohio State University
        Guy J. Brown, The University of Sheffield

An effective multipitch tracking algorithm for noisy speech is critical for
acoustic signal processing. However, the performance of existing algorithms
is not satisfactory. In this paper, we present a robust algorithm for
multipitch tracking of noisy speech. Our approach integrates an improved
channel and peak selection method, a new method for extracting periodicity
information across different channels, and a hidden Markov model (HMM) for
forming continuous pitch tracks. The resulting algorithm can reliably track
single and double pitch tracks in a noisy environment. We suggest a pitch
error measure for the multipitch situation. The proposed algorithm is
evaluated on a database of speech utterances mixed with various types of
interference. Quantitative comparisons show that our algorithm significantly
outperforms existing ones.

(13 pages, 238 KB)

for WWW:

A conference version of this technical report has been accepted by
ICASSP2002 and can be accessed by WWW:

Mingyang Wu
Perception and Neurodynamics Lab.
Department of Computer and Information Science
The Ohio State University