Natural language processing techniques for studying language in pathological ageing: A scoping review

Background In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowing for a low-cost pathology detection, classification and monitoring. Numerous research papers have been published on the automatic detection of subtle verbal alteration, starting from written texts, raw speech recordings and transcripts, and such linguistic analysis has been singled out as a cost-effective method for diagnosing dementia and other medical conditions common among elderly patients (e.g., cognitive dysfunctions associated with metabolic disorders, dysarthria). Aims To provide a critical appraisal and synthesis of evidence concerning the application of natural language processing (NLP) techniques for clinical purposes in the geriatric population. In particular, we discuss the state of the art on studying language in healthy and pathological ageing, focusing on the latest research efforts to build non-intrusive language-based tools for the early identification of cognitive frailty due to dementia. We also discuss some challenges and open problems raised by this approach. Methods & Procedures We performed a scoping review to examine emerging evidence about this novel domain. Potentially relevant studies published up to November 2021 were identified from the databases of MEDLINE, Cochrane and Web of Science. We also browsed the proceedings of leading international conferences (e.g., ACL, COLING, Interspeech, LREC) from 2017 to 2021, and checked the reference lists of relevant studies and reviews. Main Contribution The paper provides an introductory, but complete, overview of the application of NLP techniques for studying language disruption due to dementia. We also suggest that this technique can be fruitfully applied to other medical conditions (e.g., cognitive dysfunctions associated with dysarthria, cerebrovascular disease and mood disorders). Conclusions & Implications Despite several critical points need to be addressed by the scientific community, a growing body of empirical evidence shows that NLP techniques can represent a promising tool for studying language changes in pathological aging, with a high potential to lead a significant shift in clinical practice

The Automatic Extraction of Linguistic Biomarkers as a Viable Solution for the Early Diagnosis of Mental Disorders

Digital Linguistic Biomarkers extracted from spontaneous language productions proved to be very useful for the early detection of various mental disorders. This paper presents a computational pipeline for the automatic processing of oral and written texts: the tool enables the computation of a rich set of linguistic features at the acoustic, rhythmic, lexical, and morphosyntactic levels. Several applications of the instrument - for the detection of Mild Cognitive Impairments, Anorexia Nervosa, and Developmental Language Disorders - are also briefly discussed

The acquisition of the clitic ci among typically developing Italian preschoolers: preliminary data

This paper explores the acquisitional patterns of the Italian ci morpheme and its potential role as a clinical marker for Developmental Language Disorder (DLD) in Italian-speaking children, taking into account its distributional, sociolinguistic, and typological properties. To this purpose, we (i) administered a test for the elicited production of clitic pronouns in Italian – which we will refer to as “T-PEC” in the following – to 126 school-aged Italian speakers and (ii) developed a novel test focused on the ci morpheme in order to investigate its production by five-year-old typically developing children. The results and their theoretical interpretations are of particular interest since they could shed light on the acquisition of the morpheme, thus helping understand both typical and atypical grammar development. Given the continuity of the two, it could also be applied to the diagnosis and rehabilitation of DLD, which remains a major challenge for child neuropsychiatrists, psychologists, and speech-language therapists.This paper explores the acquisitional patterns of the Italian ci morpheme and its potential role as a clinical marker for Developmental Language Disorder (DLD) in Italian-speaking children, taking into account its distributional, sociolinguistic, and typological properties. To this purpose, we (i) administered a test for the elicited production of clitic pronouns in Italian – which we will refer to as “T-PEC” in the following – to 126 school-aged Italian speakers and (ii) developed a novel test focused on the ci morpheme in order to investigate its production by five-year-old typically developing children. The results and their theoretical interpretations are of particular interest since they could shed light on the acquisition of the morpheme, thus helping understand both typical and atypical grammar development. Given the continuity of the two, it could also be applied to the diagnosis and rehabilitation of DLD, which remains a major challenge for child neuropsychiatrists, psychologists, and speech-language therapists

Extraction and Classification of Acoustic Features from Italian Speaking Children with Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of complex developmental conditions whose effects and severity show high intraindividual variability. However, one of the main symptoms shared along the spectrum is social interaction impairments that can be explored through acoustic analysis of speech production. In this paper, we compare 14 Italian-speaking children with ASD and 14 typically developing peers. Accordingly, we extracted and selected the acoustic features related to prosody, quality of voice, loudness, and spectral distribution using the parameter set eGeMAPS provided by the openSMILE feature extraction toolkit. We implemented four supervised machine learning methods to evaluate the extraction performances. Our findings show that Decision Trees (DTs) and Support Vector Machines (SVMs) are the best-performing methods. The overall DT models reach a 100% recall on all the trials, meaning they correctly recognise autistic features. However, half of its models overfit, while SVMs are more consistent. One of the results of the work is the creation of a speech pipeline to extract Italian speech biomarkers typical of ASD by comparing our results with studies based on other languages. A better understanding of this topic can support clinicians in diagnosing the disorder

Analisi linguistica dei testi di un outsider. Note di metodo

Il contributo illustra la metodologia adottata per l'analisi linguistica qualitativa e quantitativa degli écrits bruts di R

Inter-Annotator Agreement in linguistica: una rassegna critica

I coefficienti di Inter-Annotator Agreement sono ampiamente utilizzati in Linguistica Computazionale e NLP per valutare il livello di “affidabilità” delle annotazioni linguistiche. L’articolo propone una breve revisione della letteratura scientifica sull’argomento.Agreement indexes are widely used in Computational Linguistics and NLP to assess the reliability of annotation tasks. The paper aims at reviewing the literature on the topic, illustrating chance-corrected coefficients and their interpretation

“ODIO TUTTO CIÒ, VOGLIO LE OSSA”: UNA PRIMA INDAGINE SULLE CARATTERISTICHE LINGUISTICHE DELLE PAGINE SOCIAL PRO-ANA IN LINGUA ITALIANA

Questo articolo presenta il primo profilo linguistico dell’Anoressia Nervosa (AN) per la lingua italiana a partire dall’analisi di pagine web pro-ana (cioè, resoconti che promuovono comportamenti alimentari potenzialmente pericolosi per la vita come la fame, il vomito autoindotto e l’abuso di lassativi). L’analisi si concentra sulle caratteristiche lessicali dei nomi utente e delle biografie, sull’uso di metafore concretizzate e sulla selezione dei deittici personali e dei morfemi di tempo nei testi. I risultati proposti mirano a far luce sulla fattibilità di trasformare le intuizioni linguistiche in uno strumento di screening computazionale su larga scala.   “I hate this, i want bones”: an initial survey of the linguistic characteristics of Italian-language pro-ana social pages This paper presents the first linguistic profile of Anorexia Nervosa (AN) for the Italian language starting from the analysis of pro-ana web pages (i.e., accounts promoting potentially life-threatening eating behaviors as life-choices such as starvation, self-induced vomiting and laxative abuse). The analysis focuses on the lexical features of usernames and bios, the usage of concretized metaphors and the selection of both personal deictics and tense morphemes in the texts. The proposed findings aim to shed light on the feasibility of turning linguistic insights into a large-scale computational screening tool

Trascrivere il parlato patologico

Il saggio, pubblicato nell'Appendice "Trascrivere le risorse orali" del volume monografico "Vademecum per il trattamento delle fonti orali" (serie: Quaderni della Rassegna degli Archivi di Stato, n.114), presenta le principali questioni associate alla trascrizione fonetica ed ortofgrafica del parlato "patologico"

Editorial: Digital linguistic biomarkers: beyond paper and pencil tests, volume II

As the co-editors of the second edition of “Digital linguistic biomarkers: beyond paper and pencil tests,” we are pleased to present this Research Topic of cutting-edge research articles that continue to explore the exciting intersection of linguistics, technology, and cognitive science. Building upon the success of our first volume in 2021 (Gagliardi et al., 2021), this new compilation delves deeper into the realm of digital linguistic biomarkers, shedding light on their evolving relevance and timeliness in the field of psychology and aging. Our first volume laid the foundation for understanding the potential of digital linguistic biomarkers in assessing various cognitive and psychological aspects. In this second volume, we witness a significant advancement in both the scope and depth of research in this area. The featured articles in this volume contribute to our understanding of how linguistic biomarkers can transcend traditional paper-and-pencil tests, offering a more nuanced and comprehensive approach to the assessment of cognitive function and psychological wellbeing