@article {157,
	title = {E-learning based Speech Therapy: generating a database of pathological speech},
	year = {2010},
	publisher = {Nederlandse Vereniging voor Fonetische Wetenschappen},
	address = {Nijmegen, The Netherlands},
	abstract = {<p>In Nijmegen, a web application for speech training in neurological patients with dysarthric speech has been developed. This web application, E-learning based Speech Therapy (EST), provides patients with diminished speech intelligibility due to neurological diseases (e.g. stroke or Parkinson{\textquoteright}s disease) with the possibility to practice speech in their own environment. The key point of the EST infrastructure is a central server, to which both therapists and patients have access. The server contains audio files of both target speech and patients{\textquoteright} pathological speech. Therapists are enabled to remotely compose a tailor-made speech training program, containing audio files of target speech. Patients have access to these files and attempt to approach the target. They can upload their own speech to the central server, thus generating a database of pathological (i.e. dysarthric) speech. Therapists are allowed to monitor their patients{\textquoteright} uploaded speech across time by downloading and analyzing speech files.</p>

<p>Apart from therapeutic benefits, EST, automatically generating a database of dysarthric speech, provides researchers in the field of speech technology with a large amount of speech data. For the purpose of developing tools for automatic error detection in speech or automatic recognition of dysarthric speech, this source of pathological speech is vital. On the long term, the results might enhance communicative independence of patients with various degrees of dysarthria. Moreover, new developments in de the field of automatic speech recognition of severely dysarthric speech might be applied in domotica.</p>
},
	author = {Lilian Beijer}
}
