Developing a Speech Recognition System for the Urdu Language

Abstract

Automatic Speech Recognition Systems (ASR) are used to convert the acoustic signals which are caught through the microphones into the sequence of words. The Automatic Speech Recognition Systems (ASR) empower the machines to react correctly, reliably, and effectively to human speech or voice and offer helpful and important services to the users. The interaction with computers or gadgets is faster, simpler, and easier, through voice or speech instead of typing through the keyboard or console, so the people will prefer Speech Recognition Systems. Speech Recognition Systems will facilitate the users in workplaces, in marketing, in banking, in health care, in language learning, and in the education field also. This project aims to design and the implementation a Speech Recognition System for the Urdu Language. In this first phase, we have collected data for the Urdu Language. To build a general Speech Recognizer, a huge amount of data is needed. In the second phase, we have implemented our System. In the final phase, we have trained and tested our Model. This model is Similar to Deep Speech 2 Models. The evaluation is carried out using Word Error Rate and Character Error Rate.