@article {155, title = {Using Speech Technology to Assist during Pathological Speech therapy}, year = {2010}, publisher = {Nederlandse Vereniging voor Fonetische Wetenschappen}, address = {Nijmegen, The Netherlands}, abstract = {

Pathological speech developing as a result of oncological treatment has a significant negative impact on the quality of life of patients. Studies have shown that improvements of speech quality and intelligibility can indeed significantly improve the quality of life of patients. To achieve these improvements in clinical treatment, the speech quality of individual patients needs to be evaluated and followed to address his or her specific problems and to collect evidence for selecting the best treatment course.

Currently, pathological speech can only be evaluated by, scarce, human judges using subjective measures. The use of panels of human judges is not feasible during routine treatment. Moreover, subjective human evaluations are less than optimal for evidence based treatment selection. Therefore, efforts have been recently made to introduce objective methods and automatic evaluations of the intelligibility and quality of pathological speech to improve reliability and reduce cost.

Two such initiatives will be discussed, from the universities of Erlangen/N{\"u}rnberg and of Gent. Both systems have been used in clinical practice. The Erlangen/N{\"u}rnberg system uses a standard ASR system trained on normal speech. The word-error-rate of the ASR is correlated to the intelligibility of the speech. The Gent system uses a speech feature recognizer trained on normal speech with a back-end that is trained to correlate recognized speech features to intelligibility.

Currently only very little is known about the way human and automatic speech recognizers {\textquotedblleft}react{\textquotedblright} to pathological speech. An obvious way to study this is to generate bench-mark synthetic speech with well defined pathologies. Recent attempt to synthesize and manipulate pathological speech for such aims will be discussed.

}, author = {Rob van Son} }