Development of Human Speech Signal-Based Intelligent Human-Computer Interface for Driving a Wheelchair in Enhancing the Quality-of-Life of the Persons
Uvanesh Kasiviswanathan, Abhishek Kushwaha, Shiru Sharma · Advances in healthcare information systems and administration book series · 2018
For the past few decades, an increase in experimental research has been carried out in enhancing the quality-of-life of the persons with different levels of disabilities. To enhance the lifestyle of differently disabled in terms of their mobility or movement or transportation, a proper aid with appropriate human-computer interface system is needed. So, in this chapter, a hybrid classification model is proposed, which combines and uses hM-GM and ANN models, for classifying human speech signal, especially the word for driving a wheelchair for helping the people, who seek transportation. For classifying the correct word from the phase of sentence (i.e., the human speech signal) to corresponding trigger command for an electrically powered wheelchair prototype, under the certain experimental condition, the hM-GM model yields good recognition of words, but they suffer major limitations as it relies on strong statistical properties and probability. Hence, by combining hM-GM and ANN model-based classifier for enhancing the accuracy of classifying the word to corresponding trigger command.