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Phase-Based Feature Representations for Improving Recognition of Dysarthric Speech., , and . SLT, page 13-20. IEEE, (2018)Personalizing synthetic voices for people with progressive speech disorders: judging voice similarity., , , and . INTERSPEECH, page 1427-1430. ISCA, (2009)Modelling the recognition of band-pass filtered speech.. University of Sheffield, UK, (2003)British Library, EThOS.Development of a Voice-Input Voice-Output Communication Aid (VIVOCA) for People with Severe Dysarthria., , , , and . ICCHP, volume 4061 of Lecture Notes in Computer Science, page 882-885. Springer, (2006)Recognising Emotions in Dysarthric Speech Using Typical Speech Data., , and . INTERSPEECH, page 4821-4825. ISCA, (2020)Dysarthric vocal interfaces with minimal training data., , , and . SLT, page 248-253. IEEE, (2014)A Framework for Collecting Realistic Recordings of Dysarthric Speech - the homeService Corpus., , , , and . LREC, European Language Resources Association (ELRA), (2016)Model adaptation and adaptive training for the recognition of dysarthric speech., and . SLPAT@Interspeech, page 65-71. Association for Computational Linguistics, (2015)Automatic selection of speakers for improved acoustic modelling: recognition of disordered speech with sparse data., , , , and . SLT, page 254-259. IEEE, (2014)An integrated toolkit deploying speech technology for computer based speech training with application to dysarthric speakers., , , , , , and . INTERSPEECH, ISCA, (2003)