Gender Identification via Voice Processing
Shivangee Kushwah1, Shantanu Singh2, Kshitij Vats3, Varsha Nemade4
1Shivangee Kushwah, Scholar, Department of Computer Science Engineering, Narsee Monjee Institute of Management Studies.
2Shantanu Singh, Scholar, Department of Computer Science Engineering, Narsee Monjee Institute of Management Studies.
3Kshitij Vats, Scholar, Department of Computer Science Engineering, Narsee Monjee Institute of Management Studies.
4Varsha Nemade, Assistant Professor, Department of Computer Science Engineering, Narsee Monjee Institute of Management Studies.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 103-105 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9525088619/2019©BEIESP | DOI: 10.35940/ijeat.F9525.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recognizing the sexual orientation of a person via speech has an assortment of utilizations going via speech investigation to customizing machine and human collaborations. Speech Recognition Technology can be installed in different continuous applications so as to expand the human-PC association. From apply autonomy to social insurance and aviation, from intelligent voice reaction frameworks to versatile communication and telematics, speech acknowledgment innovation have upgraded the human-machine connection. Sexual orientation acknowledgment is a critical part for the application implanting discourse acknowledgment as it lessens the computational intricacy for the further preparing in these applications. This paper involves extracting the constituent parts such as frequencies and interquartile ranges which are in light of a legitimate concern for distinguishing the speaker’s sexual orientation with as meager discourse as could reasonably be expected.
Keywords: Indexing-Optimization-Big Data-Artificial Intelligence