Autor:	Arshad, Syeda Rabia, Haider, Syed Mujtaba, Mughal, Abdul Basit
Rok vydání:	2022
Předmět:	Computer Science - Sound Computer Science - Machine Learning Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on the human voice biometric features like pitch, amplitude, frequency etc. We proposed an unsupervised learning model where the model can learn speech representation with limited dataset. Librispeech dataset was used in this research and we were able to achieve word error rate of 1.8. Comment: 3 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2205.14649 Zobrazit plný text záznamu View this record from Arxiv