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A Comparative Study of Pitch Detection Algorithms for Microcontroller Based Voice Pitch Detector

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This paper presents a study to compare the performance of two pitch detection algorithms namely the Auto-correlation Function and the Cepstrum Analysis to select a suitable algorithm that can be developed into a standalone voice pitch detector. The two algorithms were chosen due to their uncomplicatedness to be realized in a microcontroller. The performance of both algorithms was analyzed using 288 speech samples recorded from 24 students in both quiet and noisy environments. Results showed that both algorithms produced comparable pitch values and were able to determine the pitch of speech signals correctly. However in terms of complexity and computational processing time, the Autocorrelation Function performed better than the Cepstrum Analysis.
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Keywords: Autocorrelation Function; Cepstrum Analysis; Pitch Detection Algorithm

Document Type: Research Article

Affiliations: 1: Faculty of Engineering, Universiti Malaysia Sabah, Kota Kinabalu 88400, Malaysia 2: Artificial Intelligence Research Unit (AIRU), Universiti Malaysia Sabah, Kota Kinabalu 88400, Malaysia

Publication date: November 1, 2017

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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