automated linguistic analysis
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Oslabené sociokognitívne schopnosti môžu signalizovať riziko sociálnej (pragmatickej) komunikačnej poruchy alebo poruchy autistického spektra. Skorá identifikácia ťažkostí je kľúčová pre začatie cielenej intervencie a elimináciu prehlbovania existujúcich deficitov. Cieľom príspevku je predstaviť zahraničný diagnostický nástroj The Early Sociocognitive Battery (ESB) autoriek Shuly Chiat, Penny Roy a Jennifer Warwick, ktorý umožňuje priame hodnotenie sociokognitívnych schopností detí už v ranom veku. Teoretický opis ESB je doplnený o stručný prehľad výsledkov pilotného testovania 44 intaktných slovensky hovoriacich detí mladšieho predškolského veku, zameraného na analýzu výkonov detí v závislosti od pohlavia. Participanti boli hodnotení prostredníctvom batérie ESB, testu Opakovanie pseudoslov a Dotazníka použitia jazyka (LUI). Pilotné dáta ukazujú, že pohlavie detí nemá signifikantný vplyv na ich výkony v rámci nástroja ESB. Rovnako bola preukázaná štatisticky významná korelácia medzi celkovým skóre v dotazníku LUI a skóre v subteste Spoločná pozornosť batérie ESB. Výsledky podporujú aplikovateľnosť nástroja ESB aj v slovenskom kultúrnom a jazykovom prostredí.
Impaired sociocognitive abilities may signal the risk of a social (pragmatic) communication disorder or Autism Spectrum Disorder. Early identification of difficulties is crucial for initiating targeted intervention and preventing the escalation of existing deficits. The aim of this paper is to introduce the foreign diagnostic tool, the Early Sociocognitive Battery (ESB), developed by Shula Chiat, Penny Roy and Jennifer Warwick. This tool enables direct assessment of children's sociocognitive abilities at an early age. The theoretical description of the ESB is supplemented by a brief overview of the results from the pilot testing of 44 typically developing Slovak-speaking children in the younger preschool age group, focusing on the analysis of children's performance in relation to gender. Participants were assessed using the ESB, Nonword Repetition Task, and Language Use Inventory (LUI). Pilot data show that the children's gender does not have a significant impact on their performance within the ESB tool. In addition, a statistically significant correlation was found between the total score on the LUI and the score on the Joint Attention subtest of the ESB. The results support the applicability of the ESB tool in the Slovak cultural and linguistic context.
BACKGROUND AND OBJECTIVES: The impact of dopaminergic medication on language in Parkinson's disease (PD) remains poorly understood. This observational, naturalistic study aimed to investigate the effects of long-term dopaminergic therapy on language performance in patients with de-novo PD based on a high-level linguistic analysis of natural spontaneous discourse. METHODS: A fairy-tale narration was recorded at baseline and a 12-month follow-up. The speech samples were automatically analyzed using six representative lexical and syntactic features based on automatic speech recognition and natural language processing. RESULTS: We enrolled 109 de-novo PD patients compared to 68 healthy controls. All subjects completed the 12-month follow-up; 92 PD patients were on stable dopaminergic medication (PD-treated), while 17 PD patients remained without medication (PD-untreated). At baseline, the PD-treated group exhibited abnormalities in syntactic domains, particularly in sentence length (p = 0.018) and sentence development (p = 0.042) compared to healthy controls. After 12 months of dopaminergic therapy, PD-treated showed improvements in the syntactic domain, including sentence length (p = 0.012) and sentence development (p = 0.030). Of all PD-treated patients, 37 were on monotherapy with dopamine agonists and manifested improvement in sentence length (p = 0.048), while 32 were on monotherapy with levodopa and had no language amelioration. No changes in language parameters over time were seen in both the PD-untreated group and healthy controls. DISCUSSION: Initiation of dopaminergic therapy improved high-language syntactic deficits in de-novo PD, confirming the role of dopamine in cognitive-linguistic processing. Automated linguistic analysis of spontaneous speech via natural language processing can assist in improving the prediction and management of language deficits in PD.
- MeSH
- agonisté dopaminu * terapeutické užití MeSH
- antiparkinsonika * terapeutické užití MeSH
- dopaminové látky * terapeutické užití MeSH
- lidé středního věku MeSH
- lidé MeSH
- následné studie MeSH
- Parkinsonova nemoc * farmakoterapie komplikace MeSH
- řeč * účinky léků MeSH
- senioři MeSH
- výsledek terapie MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- pozorovací studie MeSH
BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD. METHODS: Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing. A quantitative analysis was performed using 6 lexical and syntactic and 2 acoustic features. Results were compared with human-controlled analysis to assess the robustness of the approach. Diagnostic accuracy was evaluated using sensitivity analysis. RESULTS: Despite similar disease duration, linguistic abnormalities were generally more severe in MSA than in PD, leading to high diagnostic accuracy with an area under the curve of 0.81. Compared to controls, MSA showed decreased grammatical component usage, more repetitive phrases, shorter sentences, reduced sentence development, slower articulation rate, and increased duration of pauses, whereas PD had only shorter sentences, reduced sentence development, and longer pauses. Only slower articulation rate was distinctive for MSA while unchanged for PD relative to controls. The highest correlation was found between bulbar/pseudobulbar clinical score and sentence length (r = -0.49, p = 0.002). Despite the relatively high severity of dysarthria in MSA, a strong agreement between manually and automatically computed results was achieved. DISCUSSION: Automated linguistic analysis may offer an objective, cost-effective, and widely applicable biomarker to differentiate synucleinopathies with similar clinical manifestations.
- MeSH
- diferenciální diagnóza MeSH
- lidé středního věku MeSH
- lidé MeSH
- multisystémová atrofie * diagnóza patofyziologie komplikace MeSH
- Parkinsonova nemoc * diagnóza komplikace patofyziologie MeSH
- řeč fyziologie MeSH
- senioři MeSH
- zpracování přirozeného jazyka MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: This study assessed the relationship between speech and language impairment and outcome in a multicenter cohort of isolated/idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD). METHODS: Patients with iRBD from 7 centers speaking Czech, English, German, French, and Italian languages underwent a detailed speech assessment at baseline. Story-tale narratives were transcribed and linguistically annotated using fully automated methods based on automatic speech recognition and natural language processing algorithms, leading to the 3 distinctive linguistic and 2 acoustic patterns of language deterioration and associated composite indexes of their overall severity. Patients were then prospectively followed and received assessments for parkinsonism or dementia during follow-up. The Cox proportional hazard was performed to evaluate the predictive value of language patterns for phenoconversion over a follow-up period of 5 years. RESULTS: Of 180 patients free of parkinsonism or dementia, 156 provided follow-up information. After a mean follow-up of 2.7 years, 42 (26.9%) patients developed neurodegenerative disease. Patients with higher severity of linguistic abnormalities (hazard ratio [HR = 2.35]) and acoustic abnormalities (HR = 1.92) were more likely to develop a defined neurodegenerative disease, with converters having lower content richness (HR = 1.74), slower articulation rate (HR = 1.58), and prolonged pauses (HR = 1.46). Dementia-first (n = 16) and parkinsonism-first with mild cognitive impairment (n = 9) converters had higher severity of linguistic abnormalities than parkinsonism-first with normal cognition converters (n = 17). INTERPRETATION: Automated language analysis might provide a predictor of phenoconversion from iRBD into synucleinopathy subtypes with cognitive impairment, and thus can be used to stratify patients for neuroprotective trials. ANN NEUROL 2024;95:530-543.
Verifying the speaker of a speech fragment can be crucial in attributing a crime to a suspect. The question can be addressed given disputed and reference speech material, adopting the recommended and scientifically accepted likelihood ratio framework for reporting evidential strength in court. In forensic practice, usually, auditory and acoustic analyses are performed to carry out such a verification task considering a diversity of features, such as language competence, pronunciation, or other linguistic features. Automated speaker comparison systems can also be used alongside those manual analyses. State-of-the-art automatic speaker comparison systems are based on deep neural networks that take acoustic features as input. Additional information, though, may be obtained from linguistic analysis. In this paper, we aim to answer if, when and how modern acoustic-based systems can be complemented by an authorship technique based on frequent words, within the likelihood ratio framework. We consider three different approaches to derive a combined likelihood ratio: using a support vector machine algorithm, fitting bivariate normal distributions, and passing the score of the acoustic system as additional input to the frequent-word analysis. We apply our method to the forensically relevant dataset FRIDA and the FISHER corpus, and we explore under which conditions fusion is valuable. We evaluate our results in terms of log likelihood ratio cost (Cllr) and equal error rate (EER). We show that fusion can be beneficial, especially in the case of intercepted phone calls with noise in the background.
- MeSH
- akustika řeči MeSH
- algoritmy MeSH
- lidé MeSH
- lingvistika MeSH
- pravděpodobnostní funkce MeSH
- řeč MeSH
- soudní vědy * metody MeSH
- support vector machine MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored. OBJECTIVES: We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features. METHODS: We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.5 and 120 age-, sex-, and education-matched healthy controls. Linguistic analysis was performed with fully automated methods based on automatic speech recognition and natural language processing techniques using eight lexical and syntactic features acquired from the spontaneous discourse. Fully automated annotations were compared with human annotations. RESULTS: Compared with healthy controls, lexical impairment in MS consisted of an increase in content words (p = 0.037), a decrease in function words (p = 0.007), and overuse of verbs at the expense of noun (p = 0.047), while syntactic impairment manifested as shorter utterance length (p = 0.002), and low number of coordinate clause (p < 0.001). A fully automated language analysis approach enabled discrimination between MS and controls with an area under the curve of 0.70. A significant relationship was detected between shorter utterance length and lower symbol digit modalities test score (r = 0.25, p = 0.008). Strong associations between a majority of automatically and manually computed features were observed (r > 0.88, p < 0.001). CONCLUSION: Automated discourse analysis has the potential to provide an easy-to-implement and low-cost language-based biomarker of cognitive decline in MS for future clinical trials.
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Patients with synucleinopathies frequently display language abnormalities. However, whether patients with isolated rapid eye movement sleep behavior disorder (iRBD) have prodromal language impairment remains unknown. OBJECTIVE: We examined whether the linguistic abnormalities in iRBD can serve as potential biomarkers for conversion to synucleinopathy, including the possible effect of mild cognitive impairment (MCI), speaking task, and automation of analysis procedure. METHODS: We enrolled 139 Czech native participants, including 40 iRBD without MCI and 14 iRBD with MCI, compared with 40 PD without MCI, 15 PD with MCI, and 30 healthy control subjects. Spontaneous discourse and story-tale narrative were transcribed and linguistically annotated. A quantitative analysis was performed computing three linguistic features. Human annotations were compared with fully automated annotations. RESULTS: Compared with control subjects, patients with iRBD showed poorer content density, reflecting the reduction of content words and modifiers. Both PD and iRBD subgroups with MCI manifested less occurrence of unique words and a higher number of n-grams repetitions, indicating poorer lexical richness. The spontaneous discourse task demonstrated language impairment in iRBD without MCI with an area under the curve of 0.72, while the story-tale narrative task better reflected the presence of MCI, discriminating both PD and iRBD subgroups with MCI from control subjects with an area under the curve of up to 0.81. A strong correlation between manually and automatically computed results was achieved. CONCLUSIONS: Linguistic features might provide a reliable automated method for detecting cognitive decline caused by prodromal neurodegeneration in subjects with iRBD, providing critical outcomes for future therapeutic trials. © 2022 International Parkinson and Movement Disorder Society.
Currently, dyslexia is a frequently discussed topic, which is central in many fields of science, such as special education, speech therapy, psychology, linguistics, or neuroscience. The report is a part of the international research which interconnects all the fields mentioned above. The paper presents a comparison of psychological and special-educational evaluation of adult university students/university alumni with dys-lexia and without it. In this part of the research, 27 participants were assessed by a series of six tests. The data obtained were processed in IBM SPSS Statistics 23 with the help of Multivariate analysis of variance (MANOVA). The results showed that group with dyslexia varied in their test performance aimed at reading and reading abilities, and there were no significant intelligence, attention or short-term memory differences. At the end, the report includes partial data taken from functional magnetic resonance imaging (fMRI).
- MeSH
- čtení MeSH
- dospělí MeSH
- dyslexie * diagnostické zobrazování patofyziologie MeSH
- klinická studie jako téma MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mozek diagnostické zobrazování MeSH
- neuropsychologické testy MeSH
- statistika jako téma MeSH
- studenti MeSH
- univerzity MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- Publikační typ
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
Zdravotnická dokumentace má v České republice obvykle povahu volného textu formátovaného jen pomocí mezer, tabulátorů a nových řádků. Extrakce informací z takových zpráv představuje výzvu, jejíž splnění by umožnilo její snadné využívání při poskytování zdravotní péče v zahraničí či převod do strukturované formy. Pro identifikaci a extrakci informací lze využít různých přístupů, od regulární analýzy po pokročilou lingvistickou analýzu a statistické metody. Článek shrnuje naše poznatky získané při regulární analýze a při využití běžně využívaných klasifikačních systémů.
Healthcare documentation in the Czech Republic usually has the form of a free text formatted just using spaces, tabs and line breaks. Extracting information from such a documentation is a challenge that if fulfilled would allow to use Czech medical reports by physicians with no knowledge of the Czech language as well as information transfer to a structured form. It is possible to approach this task as a task of finite-state machine, as a task of the linguistic analysis or as a task of statistics. This article summarizes our findings gained using finite-state machines and using commonly used code lists. Excerpts from real medical reports are translated to English in a way that demonstrates the same or similar problems as in the Czech language. Original Czech excerpts are available in the Czech version of this article.
- Klíčová slova
- zdravotnická dokumentace, elektronický zdravotní záznam, regulární analýza, lingvistická analýza,
- MeSH
- chorobopisy - počítačové systémy normy využití MeSH
- financování organizované MeSH
- klinické laboratorní techniky normy MeSH
- lidé MeSH
- lingvistika metody normy MeSH
- Medical Subject Headings využití MeSH
- mezinárodní klasifikace nemocí využití MeSH
- referenční standardy MeSH
- terminologie jako téma MeSH
- ukládání a vyhledávání informací metody MeSH
- zkratky jako téma MeSH
- zpracování přirozeného jazyka MeSH
- Check Tag
- lidé MeSH
... - 3.3.1.1.3 Correlations Between Components of a Random Vector 49 -- 3.3.1.1.4 Contingency-Table Analysis ... ... cf an Observation Unit -- Type I I-Classification Problem 38 -- 3.3.2.1 Configuration-Frequency Analysis ... ... 60 -- 3.3.2.2 Cluster Analysis 61 -- 3.3.2.2.1 Distance/Similarity 61 -- 3.3.2.2.1.1 Qualitative Attributes ... ... Medical Linguistics 100 -- 4.1 Medical Language •• 102 -- 4.2 Morphology ••• 102 -- 4.2.1 Elements of ... ... •••• 114 -- 4.3.2 Syntactic Analysis 118 -- 4.4 Semantics 122 -- 4.5 Metalanguages in Medicine 124 - ...
Lecture notes in medical informatics ; 14
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- MeSH
- lékařská informatika MeSH
- Publikační typ
- monografie MeSH
- Konspekt
- Lékařské vědy. Lékařství
- NLK Obory
- lékařská informatika
