Prediction of Gender Using Machine Learning
K. Ramcharan and
K. Sornalakshmi
Additional contact information
K. Ramcharan: SRM Institute of Science and Technology, Big Data Analytics
K. Sornalakshmi: SRM Institute of Science and Technology
A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1265-1274 from Springer
Abstract:
Abstract Most of the complex cellular organisms are divided into genders. Genders are of two types. Gender of an organism would be a male or a female. Each Gender has its own behavioural and physical properties. By behavioural and physical appearance of an individual, one can easily identify the gender of a person. This project deals with the identification of the gender of an individual. Voice is used in this project as an input. The individuals’ voice can be useful only if it is taken in Acoustic form. An Acoustic form of voice is the numerical value for particular speech. These numerical values are used to find patterns of voice of individuals. Different insights are drawn between attributes of voices of people and Machine Learning techniques are applied to get the results from a person’s voice.
Keywords: Acoustic; Machine learning; Age; Gender; Voice (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_128
Ordering information: This item can be ordered from
http://www.springer.com/9783030418625
DOI: 10.1007/978-3-030-41862-5_128
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().