Alternative Speech Communication System for Persons with Severe Speech Disorders

Abstract

Recommended by Juan I. Godino-Llorente Assistive speech-enabled systems are proposed to help both French and English speaking persons with various speech disorders. The proposed assistive systems use automatic speech recognition (ASR) and speech synthesis in order to enhance the quality of communication. These systems aim at improving the intelligibility of pathologic speech making it as natural as possible and close to the original voice of the speaker. The resynthesized utterances use new basic units, a new concatenating algorithm and a grafting technique to correct the poorly pronounced phonemes. The ASR responses are uttered by the new speech synthesis system in order to convey an intelligible message to listeners. Experiments involving four American speakers with severe dysarthria and two Acadian French speakers with sound substitution disorders (SSDs) are carried out to demonstrate the efficiency of the proposed methods. An improvement of the Perceptual Evaluation of the Speech Quality (PESQ) value of 5% and more than 20% is achieved by the speech synthesis systems that deal with SSD and dysarthria, respectively.

Using speech rhythm knowledge to improve dysarthric speech recognition

“…Indeed, specific parameters and configurations can be used for each level of severity. For instance, we have shown in Selouani et al (2009) that it is suitable to increase the window's length for a very severe case where the speech rate can be very low as shown in Fig. 1.…”

“…The results showed that HMMs are effective in dealing with large-scale word-length variations by some patients and SVMs brought some degree of robustness against the reduction and deletion of consonants. The speech recognition system presented in this section extends the speaker-dependent system using HMMs we have developed in Selouani et al (2009). As illustrated in 2, the process of dysarthric speech recognizer is performed subsequently to the severity level categorization.…”

“…In fact, his speech is very intelligible but his speech rate is very slow. We compare the proposed hybrid system with that presented in Selouani et al (2009). Similar experimental conditions are provided.…”

“…The first category includes statistical methods that aim at determining a likelihood function which is defined as the probability of observing the data given the model. Therefore, the probability of an observation is estimated as a function of the model, and the maximum likelihood estimate is the parameter of interests in the classification process (Selouani et al 2009;Tolba and Eltorgoman 2009). The main advantage of the statistical methods is their high recognition rate.…”

“…For the severity level assessment, we compare the hybrid system with baseline systems, namely Gaussian Mixture Models (GMMs), single MLP and standard hierarchical structure of MLPs. For recognition, an HMM phone-based system is used, and the results obtained by speaker dependent models are compared with the results reported in our previous work (Selouani et al 2009). The remainder of the paper is organized as follows.…”