SPEESH: speech-based mobile application for dysarthric speech recognition

Speech Recognition Technology for Dysarthric Speech

The initial results of investigations into the use of current commercial automatic speech recognition (ASR) software by people with speech disability (dysarthria) is presented, together with a brief summary of the history of the development of ASR and its applications for the disabled. Results confirm the viability of dysarthric use, identify areas of further investigation for improved recognit...

Deep Autoencoder Based Speech Features for Improved Dysarthric Speech Recognition

Dysarthria is a motor speech disorder, resulting in mumbled, slurred or slow speech that is generally difficult to understand by both humans and machines. Traditional Automatic Speech Recognizers (ASR) perform poorly on dysarthric speech recognition tasks. In this paper, we propose the use of deep autoencoders to enhance the Mel Frequency Cepstral Coefficients (MFCC) based features in order to ...

Adaptive Speech Recognition Framework for Dysarthric Patients

Dysarthria is a speech disorder that mostly occurs as a symptom of neurodegenerative and other neuromuscular diseases. The speech of patients with dysarthria becomes distorted, the articulation of phonemes (especially that of consonants) is poor, the intelligibility and naturalness are impaired. Because dysarthria is progressive (similarly to the other symptoms of the main disease), patients ma...

Sentence modality recognition in dysarthric speech

Modelling confusion matrices to improve speech recognition accuracy, with an application to dysarthric speech

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited vocabulary decrease speech recognition accuracy. In this paper, we introduce a technique that can increase recognition...