The paper entitled: "Proof-of-concept Evaluation of the Mobile and Personal Speech Assistant for the Recognition of Disordered Speech" by Agnieszka Bętkowska Cavalcante and Monika Grajzer

Recently, Assistive Technologies tend to exploit speech- based interfaces as a means of communication between humans and machines. While they perform very well for normal speech, their efficacy is very limited for people suffering from a variety of speech disorders, especially in the presence of environmental factors related to the disease. To overcome these issues, we have proposed a Mobile and Personal Speech Assistant (mPASS) - a platform providing the users with a set of tools, which enable to intuitively create their own automatic speech recognition system (ASR) corresponding to their needs and capabilities. The system can be designed at users’ home and tailored to the domain, vocabulary, and language they find most useful. The personalized speech recognizer can be used with diversified speech-based applications. The initial results depict the baseline performance of ASR systems created with the mPASS platform and help to identify the most accurate system set-up. Moreover, a proof-of-concept field trial shows that the mPASS speech recognition system was successfully used in the voice-controlled application, achieved high recognition accuracy and was identified by the user as better than the traditional touch input.