Multilanguage speech-based gender classification using time-frequency features and SVM classifier

• Main Authors: Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko
• Format: Book Chapter
• Language: English; English; English
• Published: Springer 2021
• Subjects: TK7885 Computer engineering
• Online Access: http://irep.iium.edu.my/86116/15/Presentation%20Schedule%20iCITES2020%202nd.pdf; http://irep.iium.edu.my/86116/21/86116_Multilanguage%20speech-based%20gender%20classification.pdf; http://irep.iium.edu.my/86116/27/86116_Multilanguage%20speech-based%20gender%20classification_SCOPUS.pdf; http://irep.iium.edu.my/86116/; https://icites2020.ump.edu.my/index.php/en/
• Institution: Universiti Islam Antarabangsa Malaysia

Speech is the most significant communication mode among human beings and a potential method for human-computer interaction (HCI). Being unparallel in complexity, the perception of human speech is very hard. The most crucial characteristic of speech is gender, and for the classification of gender oft...