=Paper=
{{Paper
|id=Vol-3878/3_main_long
|storemode=property
|title=Exploring the Use of Cohesive Devices in Dementia within an Elderly Italian Semi-spontaneous Speech Corpus
|pdfUrl=https://ceur-ws.org/Vol-3878/3_main_long.pdf
|volume=Vol-3878
|authors=Giorgia Albertin,Elena Martinelli
|dblpUrl=https://dblp.org/rec/conf/clic-it/AlbertinM24
}}
==Exploring the Use of Cohesive Devices in Dementia within an Elderly Italian Semi-spontaneous Speech Corpus==
https://ceur-ws.org/Vol-3878/3_main_long.pdf
Exploring the Use of Cohesive Devices in Dementia within
an Elderly Italian Semi-spontaneous Speech Corpus
Giorgia Albertin*,† , Elena Martinelli†
Alma Mater Studiorum - University of Bologna, Department of Classical Philology and Italian Studies, 32 Zamboni Street, 40126 Bologna, Italy
Abstract
The study of language disruption in dementia, aimed at individuating which features correlate with cognitive impairment,
is a growing area in computational linguistic research. Still, it needs a further development in analyzing some discourse
phenomena that also undergo deterioration, and can help expand our understanding of dementia-related speech and refine
automatic tools. This paper explores the discourse property of cohesion by investigating three types of cohesive devices:
reference, lexical iteration, and connectives. Ten features related to these categories have been defined and automatically
extracted from an Italian corpus of semi-spontaneous speech collected from dementia patients and healthy controls. Some of
the designed features have proven significant for the binary classification of the two groups and further quantitative analysis
highlight interesting differences in the use of cohesive devices, that seem to be associated with cognitive decline.
Keywords
Cohesion, Cohesive devices, Dementia, Cognitive Impairment, Semi-spontaneous speech
1. Introduction Coherence is compromised, especially in spontaneous
speech: the discourse appears with an abundance of ir-
Linguistics deficits commonly characterized neurodegen- relevant details and the overt difficulty to mention the
erative diseases from their onset. In Dementia, or Major key concept or to refer to the topic, resulting in a lack of
Neurocognitive Disorder (DSM-5 [1]), a syndrome of informativeness in communication [8, 9, 10].
acquired and progressive impairment in cognitive func- In recent years, speech analysis in cognitive decline
tion that interfere with independence in everyday life, has gained increasing importance in the development
language deterioration manifests itself within a broader of low-cost and portable tools for dementia screening,
framework of cognitive impairment, which could affects also supported by the remarkable advancements in Nat-
memory, visuo-spatial skills, executive functions and rea- ural Language Processing (NLP) and Machine Learning
soning. Deficits both in verbal production and compre- (ML) technologies [11]. The refinement of classification
hension have been observed, despite the specificity of systems goes hand in hand with the operationalization
different Dementia’s etiological subtypes, among which of linguistic features computed from oral productions,
the most common is Alzheimer’s Disease (AD), character- that need to be adapted to different languages. Regard-
ized with a primary impairment in episodic memory. In ing Italian, the OPLON (OPportunities for active and
AD, for example, among the well-established linguistic healthy LONgevity) [2014-2016] project was devoted to
deficits there are word-finding problems, which include the automatic extraction of an extensive group of linguis-
anomia, the production of semantic paraphasias [2, 3] and tic features from acoustic, rhythmic, readability, lexical,
the "on the-tip-of-the tongue" experience [4], low speech morpho-syntactic and syntactic levels, from a speech cor-
rate, poor word comprehension [5] and, as the disease pus of cognitively impaired patients and healthy peers
worsen, a generalized simplification of syntax [6]. Also [12, 13]. Analysis of the significance of the features high-
discourse and pragmatic level is affected by cognitive de- lighted that the acoustics ones largely correlated with
cline. Errors in referential cohesion has been registered, the cognitive state of the subjects [14].
in particular regarding ambiguous use of pronouns [7]. Expanding the list of language levels covered to in-
clude speech properties would enrich the features used
CLiC-it 2024: Tenth Italian Conference on Computational Linguistics,
for classification and, in addition, could broaden our un-
Dec 04 — 06, 2024, Pisa, Italy
*
Corresponding author. derstanding of how cognitive decline manifests itself
The contribution of each author to the paper is specified in the in verbal competence. Nevertheless, defining specific
†
CRediT authorship statement declaration. features of higher-level and complex phenomena is not
$ giorgia.albertin3@unibo.it (G. Albertin); trivial. Drawing inspiration from works that propose a
elena.martinelli12@unibo.it (E. Martinelli) "stratified" approach to discourse analysis, which indi-
https://www.unibo.it/sitoweb/giorgia.albertin3 (G. Albertin);
vidually considers macro-phenomena that intersect with
https://www.unibo.it/sitoweb/elena.martinelli12/ (E. Martinelli)
0000-0002-5728-3473 (G. Albertin); 0009-0007-4399-6951 one another [15, 16], this paper will examine cohesion,
(E. Martinelli) the property of the superficial form of the text to reflect
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0). its internal unity [17]. Cohesion assures continuity in dis-
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
Table 1
Recruitment Criteria (age; language exposure; neurological status or diagnosis; cognitive scores: MMSE, MoCA, phonemic (PF)
and semantic (SF) fluency) and Demographics (age and sex).
Control Group Pathological Group
Age > 60 years Age > 60 years
Monolingual Monolingual
Italian L1 Italian L1
Absence of neurological/sensory deficits Clinical diagnosis of dementia
Recruitment criteria
MMSE ≥ 22 MMSE < 22
MoCA > 19.262 MoCA ≤ 19.262
PF ≥ 17.35 PF < 17.35
SF ≥ 7.25 SF < 7.25
Age 81 ± 6.3 (range: 63-91) 81 ± 6.9 (range: 63-92)
Sex 12F, 8M 12F, 8M
course through a network of cohesive devices, which are
mainly words or morphemes, that contribute to maintain
semantic relations occurring in the text [17]. Therefore,
we proposed a method to design and formalize a set of
cohesion features, with the aim of observing whether
they contribute to discriminate the speech of individuals
with dementia from healthy peers. Specifically, three
types of elements, which Halliday & Hasan [18] indi-
cate among the major contributors to cohesion, were
taken into consideration: reference, lexical iteration and
connectives. The implementation of measures based on
cohesive devices is the first step towards the attempt to
include discourse properties in the automatic analysis of Figure 1: Esame del Linguaggio II [19], stimulus figure used
language in cognitive decline. The study of their interac- in the picture description task.
tion with features of other linguistic levels is crucial to
observe whether they have a positive impact on discrim-
ination between dementia subjects and healthy subjects. in the collected speech, and will be discussed in Section
The work presented in this paper, therefore, has to be in- 4 in relation to the results of the analysis.
tended as a preliminary analysis that will serve to pursue The Pathological Group (PG) consists of 20 patients
more sophisticated ML classification in the future. suffering from different forms of dementia (9 cases of
Alzheimer’s Disease, 2 of Mixed Dementia, 5 of unspeci-
2. Corpus Description fied Dementia, 3 of Vascular Dementia, 1 of Frontotempo-
ral Dementia), recruited at the “Universo Salute - Opera
In this study, we used the corpus collected within the Don Uva (PZ)” rest home, and the Control Group (CG)
project "Linguistic characteristics of the speech of el- consists of 20 subjects with neurotypical cognitive aging.
derly subjects with dementia” [20, 21], approved by the Informed consent was obtained from all participants (in
Bioethics Committee of the University of Bologna (Prot. the case of patients, by their family members, caregivers,
N. 0072032/2022). The corpus consists of oral linguistic or legal tutors). As a first step, the recruited subjects un-
production of 40 Italian-speaking individuals living in derwent an evaluation of their cognitive status through
Basilicata, forming two groups balanced by sex and age. the administration of the four following neuropsycholog-
Although the initial objective was to balance the cohorts ical tests: Mini-Mental State Examination (MMSE [22]),
also on education level, it was not possible to consider Montreal Cognitive Assesment (MoCA [23]), and Verbal
this aspect due to the lack of this information in some Fluency Test, both Phonemic [24, 25, 26, 27] and Seman-
patients medical records. Even from a sociolinguistic tic [28]. The Table 1 summarizes the recruitment criteria
perspective, it is important to advance that some par- and the demographics for study participants.
ticipants, albeit Italian-speaking, were also exposed to Then, two narrative tasks (the story of a journey and
dialect systems in their lives. This aspect explains the fre- the story of the Christmas holiday’s traditions) and one
quent occurrence of substandard linguistic expressions picture description task (using the stimulus figure in “Lan-
Table 2
Corpus Size. Audio duration and number of tokens (of the transcriptions) are reported, both with respect to the groups (Gr.
durat. and Gr. count), to the single subject (Subj. avg (st.dev)) and to the whole corpus.
Audio Tokens
Gr. durat. Subj. avg. (sd) Gr. count Subj. avg. (sd)
Pathological group 04:25:26 00:12:00 (00:08:00) 23,518 1,176 (1,218)
Control group 03:23:17 00:10:00 (00:05:00) 25,745 1,287 (710)
Total 07:48:43 - 49,263 -
guage Examination II" [19], see Figure 2) were adminis- to something already known in the text or anticipating
tered to collect semi-spontaneous speech, elicited with it. Reference functions either by repetition, which can
the following stimulus sentences: 1) "Do you want to tell be partial (e.g., through a synonym) or total, by semantic
me about a trip you took?"; 2) “How do you usually spend contiguity, or by substitution with pronouns or other
Christmas day?”; 3) “Could you describe this figure to elements [17]. It is this second type of referential ex-
me?”. This protocol allowed the collection of approxi- pressions, closely linked to the textual dimension, that is
mately 9 hours of audio (i.e., 8 hours for the recruited investigated through the features, thus focusing on the
groups and 1 hour for the interviewer), subsequently an- occurrence of anaphora and cataphora.
notated at various linguistic levels. By using the ELAN An extensive literature review was necessary to se-
software [29], the corpus was manually transcribed at lect a relevant group of those expressions in the Italian
the orthographic level, segmented into utterances (i.e., language (see [33, 34, 35]). The group of elements col-
the reference unit of discursive analysis [30]), and anno- lected includes pronouns, both personal (e.g., io, tu, lei,
tated at the prosodic level (theoretical framework: The lui), demonstrative (e.g., questo, quello), indefinite (e.g.,
Language into Act Theory - L-AcT [31]). Table 2 sum- alcuni, tutti), and possessive, possessive adjectives (e.g.,
marize the size of the corpus and the average material mio, tuo), as well as deictics (e.g., fuori, sopra, avanti, qua,
(audio/token) collected for each patient and control sub- qui, dentro, dietro, giù, indietro, su, lì, avanti, oltre, ci). The
ject. The total number of tokens was calculated on the occurrences of these groups were counted and divided by
orthographic transcription of the corpus (cleaned of an- the total number of tokens per subject (COE_REF). Addi-
notation tags), and consists of 49,263 tokens (i.e., 23,518 tionally, the pronoun density (COE_PRON_DENS), defined
for PG and 25,745 for CG). Finally, using the Gagliardi as the ratio between pronouns and nouns uttered [36],
& Tamburini pipeline [32], tokenization, lemmatization, was computed for each subject.
part-of-speech tagging, and syntactic parsing was auto-
matically performed for the entire corpus. 3.2. Lexical iteration
According to Halliday and Hasan [18], the iteration of
3. Cohesive Devices’ Features a lexical item is a specific use of the repetition-type ref-
erential mechanism, which acquires cohesive force on
Ten features that quantify the use of cohesive devices its own because it is typically used when the referent is
by the speakers were designed and formalised. The fea- farther in the text. This set of features focuses on the
tures were computed with respect to each subject, thus repetition of three main open-class categories, namely
referring to the amount of speech produced by the sin- nouns, (main) verbs, and adjectives. The use of words
gle individual in the three tasks. To comprehensively from these classes affects the richness of vocabulary, re-
address the categories of cohesive devices considered, we flecting the speaker’s tendency toward lexical variation.
use the .conll file resulted from the data annotation as Word-finding problems occurring in cognitive decline
the input for our analysis. Features’ automatic extraction often manifest as difficulties in retrieving forms from
was done via .python scripts. The methodology used the lexicon. The repetition of the same words can then
will be described in detail in the following sections. occur as a sort of repair mechanism, resulting in seman-
tically impoverished speech. Conversely, the use of some
3.1. Reference types of closed-class particles, such as prepositions and
auxiliaries, is bound to the syntactic structure.
Reference is involved when an expression that requires
Lexical iteration features were computed by sepa-
interpretation by referring to something else occurs in the
rately considering word forms and lemmas of nouns,
discourse [18]. This mechanism can be employed both
verbs, and adjectives. These features include the
in anaphoric and cataphoric uses, to refer respectively
Figure 2: Example of .conll annotation. Occurrences of automatically extracted cohesion devices are reframed: lui as a
referential expression (note the specification PronType:Prs in FEAT column), the repetition of word forms and lemma of a
verb (parlava - parlare) and the connectives e and quando.
repetitions of elements divided by the total number Table 3
of words (COE_RIP_LEM, COE_RIP_WORD), the av- Results of Kolmogorov-Smirnov test. The cohesive devices’
erage number of repetitions for repeated elements features are reported along with their p-value, significant ones
(COE_MEDRIP_LEM, COE_MEDRIP_WORD), and the max- are marked in bold. The p-values of features that resulted sig-
imum number of repetitions over the total number of nificant in Kolmogorov-Smirnov test but not after Bonferroni’s
iterations (COE_MAXRIP_LEM, COE_MAXRIP_WORD). correction are given in italic.
Features p-value
3.3. Connectives COE_TC 0.33
COE_REF 1
As defined by Ferrari [37], connectives are morpholog-
COE_REF_DENS 1
ically invariable forms (e.g., conjunctions or locutions) COE_RIP_LEM 0.04
that explicitly indicate logical relations within parts of COE_RIP_WORD 1
the text and pertain to the logical level. Elements from COE_MEDRIP_LEM 0.81
different grammatical classes can be used as connectives COE_MEDRIP_WORD 0.33
and are classified based on their function, which usually COE_MAXRIP_LEM 1
reflects their meaning (e.g., temporal, causal, additive). COE_MAXRIP_WORD 1
To compile an extensive list of connectives, we rely COE_TOT 0.04
on the Lexicon of Italian Connectives - LICO 1 [38, 39].
LICO contains 173 entries, including single words (e.g., e,
Table 4
se, ma, infatti, quando, quindi), complex expressions (e.g., Frequencies of cohesive devices by subject. The average num-
a causa di, da allora), and correlatives (e.g., da un lato ber of occurrences of substitution-type reference items, itera-
... dall’altro). Connectives are reported along with their tions of lemmas and of word forms (of nouns, adjectives and
lexical or orthographic variants, part of speech category, verbs) and connectives for each subject in PG and CG is re-
the semantic relations conveyed according to the Penn ported, along with (st. dev).
Discourse Tree Bank 3.0 schema [40], examples of usage,
Cohesive devices PG CG
and alignments of connectives from other languages. A
feature was devoted to compute the occurrences of con- Reference 146.5 (152.23) 161 (90.93)
nectives relative to the total number of tokens per subject Iter. lemma 68.9 (68.00) 87.05 (42.25)
(COE_TC). Iter. word form 74.15 (74.38) 87.8 (49.25)
Finally, the last feature was designed as an attempt Connectives 23.8 (35.15) 36.65 (26.68)
to capture the overall impact of the classes of cohesive
devices studied in this paper in the two cohorts of cor-
pus speakers. Therefore, the role of cohesion elements 4. Results
was comprehensively measured in COE_TOT by summing
referential-substitute expressions, lexical iteration items The statistical significance of the cohesion features for
and connectives, divided by the total number of words. the binary discrimination of PG and CG cohorts was cal-
Figure 3.3 shows as example an excerpt from the anno- culated using the non-parametric Kolmogorov-Smirnov
tation in .conll format, in which some of the linguistic test, due to the limited sample size of the corpus. Given
elements considered were highlighted. the number of comparisons performed, we adjusted the
results with Bonferroni correction to control for Type I
1
http://connective-lex.info/ error. This approach involves adjusting the significance
(mean=68.9), while the two values are very similar in CG
(lemmas: mean=87.05, words: mean=87.8). This imbal-
ance in favor of forms in the dementia patients appears
to uncover lexical impoverishment compared to healthy
subjects. Indeed in CG, although a higher overall number
of repetitions is registered, it is combined with a more bal-
anced distribution between lemmas and forms, suggest
greater lexical variety.
An additional consideration regarding the opposing
trend observed between lemmas and forms could be ex-
plained with respect to the sociolinguistic profile of the
data, related to the diatopic variation of Italian language
[41]. Indeed, speakers from both groups show an exten-
sive use of dialectal terms and structures characteristic of
the Italian variety spoken in the Lucanian Apennine area.
As reported in Section 2, the annotation was conducted
automatically using the pipeline developed by Gagliardi
Figure 3: Distribution plots of significantly discriminative & Tamburini [32], which is designed to analyze standard
features. COE_RIP_LEM indicates the repetitions of lemmas of Italian. Therefore, it is likely that the system struggled
nouns, adjectives and verbs and COE_TOT is a comprehensive
to handle some substandard expressions, which often
features of all the classes of cohesive devices considered.
orthographically diverge from the other words in the
transcription, as can be observed in this example from a
PG subject:
level by dividing the conventional alpha value (0.05) by
the total number of comparisons made. The results of gemm’ a trua’ [=andammo a fare visita] a mia
the test, reported in Table 3, show that two of the de- suocera, ca [=che] mio suocero è morto (. . . ).
signed features significantly contribute to differentiate
the two groups: a feature related to lemmas’ iteration It is not excluded that the presence of dialect may also
(COE_RIP_LEM) and the comprehensive feature of cohe- have influenced the automatic extraction of other co-
sive devices (COE_TOT). The distribution of these features hesive devices. Indeed, the higher frequency in CG of
is reported in Figure 4. substitution-type reference items (mean=161) and con-
The application of Bonferroni’s correction caused a nectives (mean=36.65) compared to PG (ref. mean=146.5,
decrease in the p-value of two initially significant fea- conn. mean=23.8) contrasts with what has been observed
tures, namely COE_TC and COE_MAXRIP_WORD. Given in oral production of narrative discourse in cohorts of
the exploratory nature of the experiment, which involves dementia subjects and healthy controls [8]. Therefore,
the formalisation of new features in order to discriminate we consider the possibility that automatic feature ex-
subjects with cognitive impairment from healthy con- traction preceded on manually-checked annotation may
trols in Italian, we have nevertheless chosen to highlight yield different results than those obtained.
the p-values of these features in 3. Nevertheless, the significance of the comprehensive
We can observe that, compared with the control group, feature (COE_TOT) indicates that the use of cohesive de-
the speech of dementia subjects is characterized by fewer vices investigated in this paper plays a role in distin-
repetitions of the same noun, verb and adjective lem- guishing dementia subjects from healthy controls. In
mas out of the total number of words uttered, captured Figure 4 it can be noted that COE_TOT shows, on average,
by COE_RIP_LEM. Thus in the dataset emerges that PG lower values for the PG compared to the CG. This results
group is less prone to lexical iteration of lemmas than suggests that the linguistic processing of some phenom-
CG. However, if we have a look to the occurrences’ dis- ena related to cohesion (i.e. substitution-type reference
tributions of the cohesive elements considered, reported elements, lexical iteration items, and connectives) is gen-
in Table 4, interesting trends could be noticed. Indeed, erally affected by cognitive decline in semi-spontaneous
the quantitative analysis of lexical repetitions revealed a speech. Thus, the analysis of discourse properties seems
disparity between repeated lemmas and repeated word to be a promising path for studying the linguistic charac-
forms of the same grammatical categories (noun, adjec- terisation of neurodegenerative disorders. Therefore, we
tives and verb) between the two groups. Specifically, hope that our approach in the future could be applied to
despite the high variability due to subjective differences, phenomena strictly related to cohesion - first of all, co-
it is observed that in PG, the average repetition of forms herence - or extend to other domains, such as pragmatics,
(mean=74.15) is higher than the repetition of lemmas that may mask subtle clues of cognitive frailty.
5. Conclusion a comparative review, Journal of clinical and exper-
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