Performance of WUW and general ASR speech recognition systems in different acoustic environments

Abstract

The Automatic Speech Recognition (ARS) Systems have become popular in the different areas of applications, such as education assistance, medical assistance, personal assistant, robotics and vehicles, telecommunications Industry, disabilities systems, home automation, and security access control. All these applications in life will increase the number of speech commands, which are Wake-up-words. The WUW speech recognition is similar to Key-Word spotting. However, in this paper, we propose an approach that will be used to detect the Wake-up-word (WUW) as a command with 100% accuracy and to provide a whole speech recognition system that can work in both WUW and General ASR systems with high accuracy. Also, this new ASR system will be used to solve one of the biggest problems in speech recognition, which is how to discriminate between the uses of a word or phrase in an alerting and a referential context. For example, in the use of the word “Computer'' in an alerting context is Computer, show me the chart? '' and in a referential context it is “Every computer should have a speaker. Moreover, we tested the new system with different acoustic environments, such as different background noise levels, different speaker distances to the microphone, and different speakers.