Gender Recognition of Speech based on Decision Tree Model

DOI

10.2991/iccia-19.2019.91How to use a DOI?

Keywords

Feature extraction, Decision Trees for Binary Classification, Identify gender.

Abstract

This paper introduces the decision tree binary classification algorithm to classify the gender of speech data. In speech this unstructured data, in order to recognize the gender of the input voice data by computer, it is necessary to extract the features of unstructured voice data into structured data that can be recognized by computer, and then use structured data and decision tree for binary classification to train the binary classification decision tree model. Finally, the binary classification model of decision tree is used to predict and identify the gender of structured speech data that need classification and recognition.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Biliang Zhong
AU  - Yunxin Liang
AU  - Jiyu Wu
AU  - Bisen Quan
AU  - Chunxiang Li
AU  - Wei Wang
AU  - Jincun Zhang
AU  - Zhenzhang Li
PY  - 2019/07
DA  - 2019/07
TI  - Gender Recognition of Speech based on Decision Tree Model
BT  - Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
PB  - Atlantis Press
SP  - 571
EP  - 577
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-19.2019.91
DO  - 10.2991/iccia-19.2019.91
ID  - Zhong2019/07
ER  -