Learning diagnostic models using speech and language measures
| Autor: | Colleen Richey, Jennifer M. Ogar, Dimitra Vergyri, William Jarrold, Bart Peintner, Maria Luisa Gorno Tempini |
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| Rok vydání: | 2008 |
| Předmět: |
Computer science
Speech recognition Neuropsychological Tests computer.software_genre Verbal learning Decision Support Techniques Artificial Intelligence medicine Humans Speech Diagnosis Computer-Assisted Electronic Data Processing Audio signal Language production business.industry Reproducibility of Results Linguistics Neurodegenerative Diseases Frontotemporal lobar degeneration Verbal Learning medicine.disease Frontal Lobe Sound Frontal lobe Artificial intelligence Transcription (software) business computer Psychomotor Performance Natural language processing |
| Zdroj: | 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. |
| DOI: | 10.1109/iembs.2008.4650249 |
| Popis: | We describe results that show the effectiveness of machine learning in the automatic diagnosis of certain neurodegenerative diseases, several of which alter speech and language production. We analyzed audio from 9 control subjects and 30 patients diagnosed with one of three subtypes of Frontotemporal Lobar Degeneration. From this data, we extracted features of the audio signal and the words the patient used, which were obtained using our automated transcription technologies. We then automatically learned models that predict the diagnosis of the patient using these features. Our results show that learned models over these features predict diagnosis with accuracy significantly better than random. Future studies using higher quality recordings will likely improve these results. |
| Databáze: | OpenAIRE |
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