Male Female Voice Recognition As An Initial Design For Voice Authentication Alternatives
Abstract
Full Text:
PDFReferences
P. Kumar and S. B. Rana, “Development of modified AES algorithm for data security,” Optik (Stuttg)., vol. 127, no. 4, pp. 2341–2345, 2016, doi: 10.1016/j.ijleo.2015.11.188.
H. Wu and Y. Qi, “Application of Computer Software Processing Technology in Performance Information Management System,” 2021. doi: 10.1109/IWCMC51323.2021.9498597.
R. Chavan, [1] H. Harb and L. Chen, “Voice-Based Gender Identification in Multimedia Applications,” J Intell Inf Syst, vol. 24, no. 2, pp. 179–198, 2005, doi: 10.1007/s10844-005-0322-8.
I. H. Sarker, “AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems,” SN Comput Sci, vol. 3, no. 2, Mar. 2022, doi: 10.1007/s42979-022-01043-x.
Y. Xu et al., “Artificial intelligence: A powerful paradigm for scientific research,” The Innovation, vol. 2, no. 4. Cell Press, Nov. 28, 2021. doi: 10.1016/j.xinn.2021.100179.
L. Kuang, S. Pobbathi, Y. Mansury, M. A. Shapiro, and V. K. Gurbani, “Predicting age and gender from network telemetry: Implications for privacy and impact on policy,” PLoS One, vol. 17, no. 7 July, Jul. 2022, doi: 10.1371/journal.pone.0271714.
B. S. Prasad, “GENDER CLASSIFICATION THROUGH VOICE AND PERFORMANCE ANALYSIS BY USING MACHINE LEARNING ALGORITHMS,” INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS www.ijrcar.com, vol. 7, pp. 1–11, 2019, [Online]. Available: www.ijrcar.com
P. Rani and M. B. Yadav, “A Survey on Gender and Emotion Recognition Using Voice,” 2018.
E. Rodero, “Intonation and Emotion: Influence of Pitch Levels and Contour Type on Creating Emotions,” J Voice, vol. 25, pp. e25-34, Dec. 2011, doi: 10.1016/j.jvoice.2010.02.002.
E. Wei, “Intonation Characteristics of Singing Based on Artificial Intelligence Technology and Its Application in Song-on-Demand Scoring System,” Math Probl Eng, vol. 2021, pp. 1–11, Dec. 2021, doi: 10.1155/2021/5510401.
S. Levitan, T. Mishra, and S. Bangalore, “Automatic identification of gender from speech,” Dec. 2016, pp. 84–88. doi: 10.21437/SpeechProsody.2016-18.
M. Ali, M. Islam, and M. A. Hossain, “GENDER RECOGNITION SYSTEM USING SPEECH SIGNAL,” vol. Vol.2, Dec. 2012.
H. Zimeng, M. Ylianttila, M. Liyanage, T. Advisor, and J. Okwuibe, “DEGREE PROGRAMME IN ELECTRICAL ENGINEERING or DEGREE PROGRAMME IN WIRELESS COMMUNICATIONS ENGINEERING SPEAKER GENDER RECOGNITION SYSTEM,” 2017.
D. Kaushik, N. Jain, and A. Majumdar, “Gender Voice Recognition through speech analysis with higher accuracy,” Dec. 2014. doi: 10.13140/2.1.1331.5842.
A. Raahul, R. Sapthagiri, K. Pankaj, and V. Vijayarajan, “Voice based gender classification using machine learning,” in IOP Conference Series: Materials Science and Engineering, Dec. 2017, vol. 263, no. 4. doi: 10.1088/1757-899X/263/4/042083.
R. Ihaka and R. Gentleman, “R: A Language for Data Analysis and Graphics,” Journal of Computational and Graphical Statistics, vol. 5, no. 3, pp. 299–314, 1996, doi: 10.2307/1390807.
J. Doi, “Web Application Teaching Tools for Statistics Using R and Shiny,” Technology Innovations in Statistics Education, vol. 9, pp. 1–32, Dec. 2016.
J. Wojciechowski, A. Hopkins, and R. Upton, “Interactive Pharmacometric Applications Using R and the Shiny Package,” CPT Pharmacometrics Syst Pharmacol, vol. 4, pp. 146–159, Dec. 2015, doi: 10.1002/psp4.21.
X. Wu et al., “Top 10 algorithms in data mining,” Knowl Inf Syst, vol. 14, no. 1, pp. 1–37, 2008, doi: 10.1007/s10115-007-0114-2.
A. K. and S. Aithal, “Voice Biometric Systems for User Identification and Authentication – A Literature Review,” International Journal of Applied Engineering and Management Letters, pp. 198–209, Dec. 2022, doi: 10.47992/IJAEML.2581.7000.0131.
Y. Taspinar, M. SARITAŞ, I. Cinar, and M. Koklu, “Gender Determination Using Voice Data,” International Journal of Applied Mathematics Electronics and Computers, pp. 232–235, Dec. 2020, doi: 10.18100/ijamec.809476.
T.-H. Li, “Quantile-Frequency Analysis and Deep Learning for Signal Classiication,” 2022, doi: 10.21203/rs.3.rs-1855496/v1.
H. Elo€, C. Frouin-Mouy, and M. O. Hammill, “In-air and underwater sounds of hooded seals during the breeding season in the Gulf of St. Lawrence,” 2021, doi: 10.1121/10.
Z. Y, “Application of Data Mining Techniques in the Analysis of Acoustic Sound Characteristics,” J Inf Technol Softw Eng, vol. 08, no. 03, 2018, doi: 10.4172/2165-7866.1000238.
S. Kushwah, S. Singh, K. Vats, and V. Nemade, “Gender Identification Via Voice Analysis,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, pp. 746–753, Dec. 2019, doi: 10.32628/CSEIT1952188.
S. Sanjay, T. B. Student, and T. B. Kute Researcher, “PERFORMANCE EVALUATION OF ALGORITHMS FOR GENDER CLASSIFICATION,” 2020. [Online]. Available: http://www.ijeast.com
J. Kaur and J. Singh Gurm, “Optimizing the Accuracy of CART Algorithm by Using Genetic Algorithm,” International Journal of Computer Science Trends and Technology, vol. 3, 2013, [Online]. Available: www.ijcstjournal.org
E. Ersoy, E. Albey, and E. Kayış, “A CART-based genetic algorithm for constructing higher accuracy decision trees,” in DATA 2020 - Proceedings of the 9th International Conference on Data Science, Technology and Applications, 2020, pp. 328–338. doi: 10.5220/0009893903280338.
M. Araya-Salas and G. Smith-Vidaurre, “warbleR: an r package to streamline analysis of animal acoustic signals,” Methods Ecol Evol, vol. 8, no. 2, pp. 184–191, Feb. 2017, doi: 10.1111/2041-210X.12624.
lakhan jasuja and akhtar rasool, “Voice Gender Recognizer RECOGNITION OF GENDER FROM VOICE USING DEEP NEURAL NETWORKS,” Proceedings, International Conference on Smart Electronics and Communication (ICOSEC 2020) : 10-12, September 2020, 2020.
“Analysis of Fashion Industry Business Environment,” Latest Trends Text. Fash. Des., vol. 2, no. 4, 2018, doi: 10.32474/lttfd.2018.02.000144.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.