ML enhances Human Speech Recognition

Published Categorized as Artificial Intelligence

Hearing loss is one of the main issue in the present era. According to World Health Organization, almost 430 million from the entire world are suffering from hearing loss. Many researchers are continuously striving to study the ability of the people in order to recognize the human speech. The humans are unable to recognize the speech if there is no echo. Overall, the people suffering from hearing loss are unable to find out the educational opportunities in the society. Apart from it, they have to face social withdrawal due to difficulty in communicating with others and leading to the loss of self-confidence. Hence ML enhances human speech recognition through different algorithms.

In order to overcome the issue, the researchers are finding out the best solution to it. Hence the Acoustical Society of America through AIP Publishing has published The Journal of Acoustical Society of America. According to the journal, the researchers operating in Germany have investigated a human speech recognition model. The model is entirely based on the machine learning.

How ML enhances Human speech Recognition

The algorithms which work in Human speech recognition of ML include PLP features, Viterbi search, deep neural networks, discrimination training and as well as WEST framework. As far as the human speech model is concerned, the user has to input the voice or inserted text which in turn enables the machine to respond. The human speech recognition model is able to recognize the voice pattern, tone and as well as the frequency.

In order to see the proper functioning, the researchers have conducted an experiment. The experiment included 8 normal hearing listeners and 20 impaired hearing listeners. As a result, the listeners experienced noticeable improvements in the voices through the use of human speech recognition model.

ML model is easily accessible and easy to use. Furthermore, human speech recognition model can help in boosting the productivity of many businesses. It acts as a machine to human model which helps in enhancing the social exposure of the individuals suffering from hear loss. Thus it enables them to build their self confidence.


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