Analysis of spontaneous speech in Parkinson's disease by natural language processing
Patients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using autom...
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| Published in | Parkinsonism & related disorders Vol. 113; p. 105411 |
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| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Ltd
01.08.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1353-8020 1873-5126 1873-5126 |
| DOI | 10.1016/j.parkreldis.2023.105411 |
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| Abstract | Patients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using automated morphological analysis tools.
We enrolled 53 PD patients with normal cognitive function and 53 HC, and assessed their spontaneous speech using natural language processing. Machine learning algorithms were used to identify the characteristics of spontaneous conversation in each group. Thirty-seven features focused on part-of-speech and syntactic complexity were used in this analysis. A support-vector machine (SVM) model was trained with ten-fold cross-validation.
PD patients were found to speak less morphemes on one sentence than the HC group. Compared to HC, the speech of PD patients had a higher rate of verbs, case particles (dispersion), and verb utterances, and a lower rate of common noun utterances, proper noun utterances, and filler utterances. Using these conversational changes, the respective discrimination rates for PD or HC were more than 80%.
Our results demonstrate the potential of natural language processing for linguistic analysis and diagnosis of PD.
•Spontaneous speech of patients with Parkinson's diseases (PD) was analyzed.•PD patients spoke less morphemes on one sentence than the healthy controls.•PD patients had a higher rate of verbs and a lower rate of noun than controls.•Discrimination accuracy rates using identified language items were more than 80%. |
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| AbstractList | Patients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using automated morphological analysis tools.INTRODUCTIONPatients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using automated morphological analysis tools.We enrolled 53 PD patients with normal cognitive function and 53 HC, and assessed their spontaneous speech using natural language processing. Machine learning algorithms were used to identify the characteristics of spontaneous conversation in each group. Thirty-seven features focused on part-of-speech and syntactic complexity were used in this analysis. A support-vector machine (SVM) model was trained with ten-fold cross-validation.METHODSWe enrolled 53 PD patients with normal cognitive function and 53 HC, and assessed their spontaneous speech using natural language processing. Machine learning algorithms were used to identify the characteristics of spontaneous conversation in each group. Thirty-seven features focused on part-of-speech and syntactic complexity were used in this analysis. A support-vector machine (SVM) model was trained with ten-fold cross-validation.PD patients were found to speak less morphemes on one sentence than the HC group. Compared to HC, the speech of PD patients had a higher rate of verbs, case particles (dispersion), and verb utterances, and a lower rate of common noun utterances, proper noun utterances, and filler utterances. Using these conversational changes, the respective discrimination rates for PD or HC were more than 80%.RESULTSPD patients were found to speak less morphemes on one sentence than the HC group. Compared to HC, the speech of PD patients had a higher rate of verbs, case particles (dispersion), and verb utterances, and a lower rate of common noun utterances, proper noun utterances, and filler utterances. Using these conversational changes, the respective discrimination rates for PD or HC were more than 80%.Our results demonstrate the potential of natural language processing for linguistic analysis and diagnosis of PD.CONCLUSIONSOur results demonstrate the potential of natural language processing for linguistic analysis and diagnosis of PD. Patients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using automated morphological analysis tools. We enrolled 53 PD patients with normal cognitive function and 53 HC, and assessed their spontaneous speech using natural language processing. Machine learning algorithms were used to identify the characteristics of spontaneous conversation in each group. Thirty-seven features focused on part-of-speech and syntactic complexity were used in this analysis. A support-vector machine (SVM) model was trained with ten-fold cross-validation. PD patients were found to speak less morphemes on one sentence than the HC group. Compared to HC, the speech of PD patients had a higher rate of verbs, case particles (dispersion), and verb utterances, and a lower rate of common noun utterances, proper noun utterances, and filler utterances. Using these conversational changes, the respective discrimination rates for PD or HC were more than 80%. Our results demonstrate the potential of natural language processing for linguistic analysis and diagnosis of PD. Patients with Parkinson's disease (PD) encounter a variety of speech-related problems, including dysarthria and language disorders. To elucidate the pathophysiological mechanisms for linguistic alteration in PD, we compared the utterance of patients and that of healthy controls (HC) using automated morphological analysis tools. We enrolled 53 PD patients with normal cognitive function and 53 HC, and assessed their spontaneous speech using natural language processing. Machine learning algorithms were used to identify the characteristics of spontaneous conversation in each group. Thirty-seven features focused on part-of-speech and syntactic complexity were used in this analysis. A support-vector machine (SVM) model was trained with ten-fold cross-validation. PD patients were found to speak less morphemes on one sentence than the HC group. Compared to HC, the speech of PD patients had a higher rate of verbs, case particles (dispersion), and verb utterances, and a lower rate of common noun utterances, proper noun utterances, and filler utterances. Using these conversational changes, the respective discrimination rates for PD or HC were more than 80%. Our results demonstrate the potential of natural language processing for linguistic analysis and diagnosis of PD. •Spontaneous speech of patients with Parkinson's diseases (PD) was analyzed.•PD patients spoke less morphemes on one sentence than the healthy controls.•PD patients had a higher rate of verbs and a lower rate of noun than controls.•Discrimination accuracy rates using identified language items were more than 80%. |
| ArticleNumber | 105411 |
| Author | Hattori, Makoto Hiraga, Keita Katsuno, Masahisa Satake, Yuki Iribe, Yurie Tanaka, Yasuhiro Sato, Maki Kitaoka, Norihide Yokoi, Katsunori Tsuboi, Takashi Hori, Akihiro |
| Author_xml | – sequence: 1 givenname: Katsunori surname: Yokoi fullname: Yokoi, Katsunori email: katsu-y@ncgg.go.jp organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 2 givenname: Yurie surname: Iribe fullname: Iribe, Yurie email: iribe@ist.aichi-pu.ac.jp organization: School of Information Science and Technology, Aichi Prefectural University, Nagakute, Japan – sequence: 3 givenname: Norihide surname: Kitaoka fullname: Kitaoka, Norihide email: kitaoka@tut.jp organization: Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan – sequence: 4 givenname: Takashi surname: Tsuboi fullname: Tsuboi, Takashi email: takashi80@gmail.com organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 5 givenname: Keita surname: Hiraga fullname: Hiraga, Keita email: gance2000@googlemail.com organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 6 givenname: Yuki surname: Satake fullname: Satake, Yuki email: y.satake0316@gmail.com organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 7 givenname: Makoto surname: Hattori fullname: Hattori, Makoto email: hattori.makoto@b.mbox.nagoya-u.ac.jp organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 8 givenname: Yasuhiro surname: Tanaka fullname: Tanaka, Yasuhiro email: acv27470@nyc.odn.ne.jp organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 9 givenname: Maki surname: Sato fullname: Sato, Maki email: mi.suenyo.0013@gmail.com organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan – sequence: 10 givenname: Akihiro surname: Hori fullname: Hori, Akihiro email: a.hori@gfkosei.or.jp organization: Kumiai Kosei Hospital, Takayama, Gifu, Japan – sequence: 11 givenname: Masahisa orcidid: 0000-0001-9453-9311 surname: Katsuno fullname: Katsuno, Masahisa email: ka2no@med.nagoya-u.ac.jp organization: Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan |
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| Keywords | Spontaneous speech Natural language processing Parkinson's disease Linguistic analysis Part-of-speech |
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