JOURNAL ARTICLE

Fundamental frequency estimation using modified higher order moments and multiple windows

Abstract

This paper proposes a set of higher-order modified moments for estimation of the fundamental frequency of speech and explores the impact of the speech window length on pitch estimation error. The pitch extraction methods are evaluated in a range of noise types and SNRs. For calculation of errors, pitch reference values are calculated from manually-corrected estimates of the periods obtained from laryngograph signals. The results obtained for the 3rd and 4th order modified moment compare well with methods based on correlation and magnitude difference criteria and the YIN method; with improved pitch accuracy and less occurrence of large errors

Keywords:
Moment (physics) Range (aeronautics) Fundamental frequency Pitch detection algorithm Noise (video) Set (abstract data type) Computer science Method of moments (probability theory) Mathematics Estimation Algorithm Speech recognition Statistics Speech processing Acoustics Physics Artificial intelligence Engineering

Metrics

2
Cited By
0.31
FWCI (Field Weighted Citation Impact)
0
Refs
0.49
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence

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