Using Automatic Speech Processing to Analyze Fundamental Frequency of Child-Directed Speech Stored in a Very Large Audio Corpus

被引:0
作者
De Palma, Paul [1 ]
VanDam, Mark [2 ]
机构
[1] Gonzaga Univ, Dept Comp Sci, Spokane, WA 99258 USA
[2] Washington State Univ, HOPE, Elson S Floyd Coll Med, Dept Speech & Hearing Sci, Spokane, WA USA
来源
2017 JOINT 17TH WORLD CONGRESS OF INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND 9TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (IFSA-SCIS) | 2017年
关键词
child-directed speech; automatic speech processing; LENA; big data; fundamental frequency;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Child-Directed-Speech (CDS) is associated with raised fundamental frequency (f(0)). In a previous paper we claimed that f(0) could be extracted from 500 hours of audio recordings using soft computing techniques and that mothers, but not fathers, increase f(0) in CDS. Using an audio corpus more than ten times larger, this paper reports that fathers do raise f(0) but not as much as mothers. The principle finding is a proof of concept: 1) very large speech corpora, unavailable until recently, can be processed using soft computing techniques; 2) the use of very large corpora may force revisions of conclusions based on smaller datasets.
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页数:6
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