Open AccessPerformance Evaluation of Novel AMDF‐Based Pitch Detection Scheme
Author(s) -
Kumar Sandeep
Publication year - 2016
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.16.0115.0926
Subject(s) - cepstrum , intelligibility (philosophy) , speech recognition , computer science , autocorrelation , pitch detection algorithm , waveform , mel frequency cepstrum , artificial intelligence , speech processing , feature extraction , mathematics , telecommunications , philosophy , statistics , radar , epistemology
A novel average magnitude difference function (AMDF)‐based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real‐time implementation of a speech analysis‐synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum‐, ACF‐, AMDF‐, and CAMDF‐based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum‐, ACF‐, and CAMDF‐based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF‐ and cepstrum‐based PDSs.