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@inProceedings{lundholmfors-etal-2019-reading-284036,
	title        = {Reading and mild cognitive impairment},
	abstract     = {In the present study, we investigated the discriminatory power of eye-tracking features in distinguishing between individuals with mild cognitive impairment (MCI) and healthy controls (HC). The eye movements of the study participants were recorded at two different time points, 18 months apart. Using a machine learning approach with leave-one-out cross-validation, we were able to discriminate between the groups with 73.6 AUC. However, somewhat surprisingly the classification was less successful using data from the second recording session, which might be attributed to the non-static nature of cognitive status. Still, the outcome suggests that eye-tracking measures can be exploited as useful markers of MCI.
},
	booktitle    = {Proceedings of the 10th International Conference of Experimental Linguistics, 25-27 September 2019, Lisbon, Portugal},
	editor       = {Antonis Botinis},
	author       = {Lundholm Fors, Kristina and Antonsson, Malin and Kokkinakis, Dimitrios and Fraser, Kathleen},
	year         = {2019},
	ISBN         = {978-618-84585-0-5},
}

@inProceedings{johansson-etal-2019-lexical-284330,
	title        = {Lexical diversity and mild cognitive impairment},
	abstract     = {This paper explores the role that various lexical-based measures play for differentiating between individuals with mild forms of cognitive impairment (MCI) and healthy controls (HC). Recent research underscores the importance of language and linguistic analysis as essential components that can contribute to a variety of sensitive cognitive measures for the identification of milder forms of cognitive
impairment. Subtle language changes serve as a sign that an individual’s cognitive functions have been impacted, potentially leading to early diagnosis. Our research aims to identify linguistic biomarkers that could distinguish between individuals with MCI and HC and also be useful in predicting MCI.},
	booktitle    = {Proceedings of the 10th International Conference of Experimental Linguistics, 25-27 September 2019, Lisbon, Portugal},
	editor       = {Antonis Botinis},
	author       = {Johansson, Sofie and Lundholm Fors, Kristina and Antonsson, Malin and Kokkinakis, Dimitrios},
	year         = {2019},
	publisher    = {ExLing Society},
	address      = {Athens, Greece},
	ISBN         = {978-618-84585-0-5},
}

@inProceedings{antonsson-etal-2019-discourse-284038,
	title        = {Discourse in Mild Cognitive Impairment },
	abstract     = {This paper reports on how persons with mild cognitive impairment (MCI) perform on two types of narrative tasks compared to a group of healthy controls (HC). The first task is a widely used picture description task and the other task is a more complex discourse task. Since the latter task puts higher demands on cognitive linguistic skills, as seen in previous research, we expected this task to be more efficient in discriminating between the two groups. The results confirm this hypothesis. 
},
	booktitle    = {Proceedings of the 10th International Conference of Experimental Linguistics, 25-27 September 2019, Lisbon, Portugal},
	editor       = {Antonis Botinis},
	author       = {Antonsson, Malin and Lundholm Fors, Kristina and Kokkinakis, Dimitrios},
	year         = {2019},
	publisher    = { ExLing Society},
	ISBN         = {978-618-84585-0-5},
}

@inProceedings{kokkinakis-lundholmfors-2020-digital-295582,
	title        = {Digital Neuropsychological Tests and Biomarkers: Resources for NLP and AI Exploration in the Neuropsychological Domain},
	abstract     = {Non-invasive, time and cost-effective, easy-to-measure techniques for the early diagnosis or monitoring the progression of brain and mental disorders are at the forefront of recent research in this field. Natural Language Processing and Artificial Intelligence can play an important role in supporting and enhancing data driven approaches to improve the accuracy of prediction and classification. However, large datasets of e.g. recorded speech in the domain of cognitive health are limited. To improve the performance of existing models we need to train them on larger datasets, which could raise the accuracy of clinical diagnosis, and contribute to the detection of early signs at scale. In this paper, we outline our ongoing work to collect such data from a large population in order to support and conduct future research for modelling speech and language features in a cross-disciplinary manner. The final goal is to explore and combine linguistic with multimodal biomarkers from the same population and compare hybrid models that could increase the predictive accuracy of the algorithms that operate on them.},
	booktitle    = {CLARIN Annual Conference 2020 in Virtual Form},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina},
	year         = {2020},
}

@article{kokkinakis-lundholmfors-2020-manga-294522,
	title        = {Hur många djur du kommer på kan avslöja hur din hjärna mår},
	journal      = {Språkbruk},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina},
	year         = {2020},
	volume       = {2},
	pages        = {48--51},
}

@inProceedings{fraser-etal-2019-multilingual-280280,
	title        = {Multilingual prediction of Alzheimer’s disease through domain adaptation and concept-based language modelling},
	abstract     = {There is growing evidence that changes in speech and language may be early markers of dementia, but much of the previous NLP work in this area has been limited by the size of the available datasets. Here, we compare several methods of domain adaptation to augment a small French dataset of picture descriptions (n = 57) with a much larger English dataset (n = 550), for the task of automatically distinguishing participants with dementia from controls. The first challenge is to identify a set of features that transfer across languages; in addition to previously used features based on information units, we introduce a new set of features to model the order in which information units are produced by dementia patients and controls. These concept-based language model features improve classification performance in both English and French separately, and the best result (AUC = 0.89) is achieved using the multilingual training set with a combination of information and language model features.},
	booktitle    = {Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), June 2 - June 7, 2019, Minneapolis, Minnesota /  Jill Burstein, Christy Doran, Thamar Solorio (Editors) },
	author       = {Fraser, Kathleen and Linz, Nicklas and Lundholm Fors, Kristina and Rudzicz, Frank and König, Alexandra and Alexandersson, Jan and Robert, Philippe and Kokkinakis, Dimitrios},
	year         = {2019},
	publisher    = {Association for Computational Linguistics},
	address      = {Stroudsburg, PA },
	ISBN         = {978-1-950737-13-0},
}

@inProceedings{linz-etal-2019-temporal-279131,
	title        = {Temporal Analysis of Semantic Verbal Fluency Tasks in Persons with Subjective and Mild Cognitive Impairment.},
	abstract     = {The Semantic Verbal Fluency (SVF) task is a classical neuropsychological assessment where persons are asked to produce words belonging to a semantic category (e.g., animals) in a given time. This paper introduces a novel method of temporal analysis for SVF tasks utilizing time intervals and applies it to a corpus of elderly Swedish subjects (mild cognitive impairment, subjective cognitive impairment and healthy controls). A general decline in word count and lexical frequency over the course of the task is revealed, as well as an increase in word transition times. Persons with subjective cognitive impairment had a higher word count during the last intervals, but produced words of the same lexical frequencies. Persons with MCI had a steeper decline in both word count and lexical frequencies during the third interval. Additional correlations with neuropsychological scores suggest these findings are linked to a person’s overall vocabulary size and processing speed, respectively. Classification results improved when adding the novel features (AUC = 0.72), supporting their diagnostic value.},
	booktitle    = {Sixth Workshop on Computational Linguistics and Clinical Psychology: Reconciling Outcomes. Minneapolis, Minnesota,  USA,  June 6, 2019 / Kate Niederhoffer, Kristy Hollingshead, Philip Resnik, Rebecca Resnik, Kate Loveys (Editors)},
	author       = {Linz, Nicklas and Lundholm Fors, Kristina and Lindsay, Hali and Eckerström, Marie and Alexandersson, Jan and Kokkinakis, Dimitrios},
	year         = {2019},
	publisher    = {Association for Computational Linguistics },
	address      = {Stroudsburg, PA },
	ISBN         = {978-1-948087-95-7},
}

@article{fraser-etal-2019-predicting-282807,
	title        = {Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers},
	abstract     = {Recent work has indicated the potential utility of automated language analysis for the detection of mild cognitive impairment (MCI). Most studies combining language processing and machine learning for the prediction of MCI focus on a single language task; here, we consider a cascaded approach to combine data from multiple language tasks. A cohort of 26 MCI participants and 29 healthy controls completed three language tasks: picture description, reading silently, and reading aloud. Information from each task is captured through different modes (audio, text, eye-tracking, and comprehension questions). Features are extracted from each mode, and used to train a series of cascaded classifiers which output predictions at the level of features, modes, tasks, and finally at the overall session level. The best classification result is achieved through combining the data at the task level (AUC = 0.88, accuracy = 0.83). This outperforms a classifier trained on neuropsychological test scores (AUC = 0.75, accuracy = 0.65) as well as the "early fusion" approach to multimodal classification (AUC = 0.79, accuracy = 0.70). By combining the predictions from the multimodal language classifier and the neuropsychological classifier, this result can be further improved to AUC = 0.90 and accuracy = 0.84. In a correlation analysis, language classifier predictions are found to be moderately correlated (rho = 0.42) with participant scores on the Rey Auditory Verbal Learning Test (RAVLT). The cascaded approach for multimodal classification improves both system performance and interpretability. This modular architecture can be easily generalized to incorporate different types of classifiers as well as other heterogeneous sources of data (imaging, metabolic, etc.).},
	journal      = {Frontiers in Aging Neuroscience},
	author       = {Fraser, Kathleen and Lundholm Fors, Kristina and Eckerström, Marie and Öhman, Fredrik and Kokkinakis, Dimitrios},
	year         = {2019},
	volume       = {11},
	number       = {205},
}

@inProceedings{kokkinakis-lundholmfors-2019-"hund-279384,
	title        = {"hund, katt, ko...": Semantiskt ordflödestest som indikator på kognitiv nedsättning hos äldre.},
	abstract     = {Ordflödestest är en typ av test som ofta ingår vid språkliga och neuropsykologiska utredningar, och de används för att bedöma språkliga förmågor, så som ordmobilisering, och exekutiva funktioner, så som verbalt arbetsminne och bearbetningshastighet. Vid ett fonologiskt ordflödestest får personen i uppgift att på en begränsad tid (oftast 60 sekunder) producera så många ord som möjlighet som börjar med en viss bokstav (ofta F, A och S), medan vid ett semantiskt ordflödestest får personen istället i uppgift att producera ord som tillhör en viss kategori (t ex djur eller grönsaker). Dessa tester tar liten tid att genomföra, är lätta att administrera och ger värdefull information om kognitiva färdigheter och begränsningar.  Tidigare forskning har visat att ordflödestester har hög reliabilitet och är känsliga för kognitiva nedsättningar. Vid analys av testen mäts traditionellt enbart antalet korrekta ord som producerats, men med hjälp av digital ljudinspelning samt den utveckling som skett inom språkteknologi kan man nu göra mer detaljerade analyser och få ny information om de strategier man använder vid exempelvis ordgenereringen; nämligen klustring (produktion av en grupp relaterade ord inom den redan identifierade subkategorin) och växling (sökning efter och växling till nya subkategorier). I vår forskning studerar vi bl.a. semantiskt ordflödestest som nyanserad indikator på olika aspekter av exekutiva och språkliga förmågor hos personer med degenerativa lindriga eller milda kognitiva nedsättningar samt en kontrollgrupp med kognitivt friska individer. Studien kommer presentera detaljer av vår språkteknologiska analys, visa på de skillnader som finns mellan grupperna och de samband som eventuellt finns med andra, redan genomförda, neuropsykiatriska tester för samma population.},
	booktitle    = {Svenskans beskrivning 37, 8–10.5.2019, Åbo, Finland.},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina},
	year         = {2019},
}

@inProceedings{kokkinakis-etal-2019-multifaceted-278217,
	title        = {A Multifaceted Corpus for the Study of Cognitive Decline in a Swedish Population},
	abstract     = {A potential, early-stage diagnostic marker for neurodegenerative diseases, such as Alzheimer’s disease, is the onset of language disturbances which is often characterized by subtle word-finding difficulties, impaired spontaneous speech, slight speech hesitancy, object naming difficulties and phonemic errors. Connected speech provides valuable information in a non-invasive and easy-to-assess way for determining aspects of the severity of language impairment. Data elicitation is an established method of obtaining highly constrained samples of connected speech that allows us to study the intricate interactions between various linguistic levels and cognition. In the paper, we describe the collection and content of a corpus consisting of spontaneous Swedish speech from individuals with Mild Cognitive Impairment (MCI), with Subjective Cognitive Impairment SCI) and healthy, age-matched controls (HC). The subjects were pooled across homogeneous subgroups for age and education, a sub-cohort from the Gothenburg-MCI study. The corpus consists of high quality audio recordings (including transcriptions) of several tasks, namely:
(i)	a picture description task – the Cookie-theft picture, an ecologically valid approximation to spontaneous discourse that has been widely used to elicitate speech from speakers with different types of language and communication disorders; 
(ii)	a read aloud task (including registration of eye movements) – where participants read a text from the IREST collection twice, both on a computer screen (while eye movements are registered), and the same text on paper;
(iii)	a complex planning task – a subset of executive functioning that tests the ability to identify, organize and carry out (complex) steps and elements that are required to achieve a goal;
(iv)	a map task – a spontaneous speech production/semi-structured conversation in which the participants are encouraged to talk about a predefined, cooperative task-oriented topic;
(v)	a semantic verbal fluency task – category animals: where participants have to produce as many words as possible from a category in a given time (60 seconds). The fluency tests require an elaborate retrieval of words from conceptual (semantic) and lexical (phonetic) memory involving specific areas of the brain in a restricted timeframe. 
All samples are produced by Swedish speakers after obtaining written consent approved by the local ethics committee. Tasks (i) and (ii) have been collected twice in a diachronically apart period of 18 months between 2016 and 2018.
The corpus represents an approximation to speech in a natural setting: The material for elicitation is controlled in the sense that the speakers are given specific tasks to talk about, and they do so in front of a microphone. The corpus may serve as a basis for many linguistic and/or speech technological investigations and has being already used for various investigations of language features.},
	booktitle    = {CLARe4 : Corpora for Language and Aging Research, 27 February – 1 March 2019, Helsinki, Finland},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Fraser, Kathleen and Eckerström, Marie and Horn, Greta and Themistocleous, Charalambos},
	year         = {2019},
}

@inProceedings{fraser-etal-2018-improving-264397,
	title        = {Improving the Sensitivity and Specificity of MCI Screening with Linguistic Information.},
	abstract     = {The Mini-Mental State Exam (MMSE) is a screening tool for cognitive impairment. It has been extensively validated and is widely used, but has been criticized as not being effective in detecting mild cognitive impairment (MCI). In this study, we examine the utility of augmenting MMSE scores with automatically extracted linguistic information from a narrative speech task to better differentiate between individuals with MCI and healthy controls in a Swedish population. We find that with the addition of just four linguistic features, the F score (measuring a trade-off between sensitivity and specificity) is improved from 0.67 to 0.81 in logistic regression classification. These preliminary results suggest that the accuracy of traditional screening tools may be improved through the addition of computerized language analysis.},
	booktitle    = {Proceedings of the LREC workshop: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID-2). 8th  of May 2018,  Miyazaki, Japan  / Dimitrios  Kokkinakis  (ed.)},
	author       = {Fraser, Kathleen and Lundholm Fors, Kristina and Eckerström, Marie and Themistocleous, Charalambos and Kokkinakis, Dimitrios},
	year         = {2018},
	ISBN         = {979-10-95546-26-9},
}

@article{fraser-etal-2019-multilingual-270713,
	title        = {Multilingual word embeddings for the assessment of narrative speech in mild cognitive impairment},
	abstract     = {We analyze the information content of narrative speech samples from individuals with mild cognitive impairment (MCI), in both English and Swedish, using a combination of supervised and unsupervised learning techniques. We extract information units using topic models trained on word embeddings in monolingual and multilingual spaces, and find that the multilingual approach leads to significantly better classification accuracies than training on the target language alone. In many cases, we find that augmenting the topic model training corpus with additional clinical data from a different language is more effective than training on additional monolingual data from healthy controls. Ultimately we are able to distinguish MCI speakers from healthy older adults with accuracies of up to 63% (English) and 72% (Swedish) on the basis of information content alone. We also compare our method against previous results measuring information content in Alzheimer's disease, and report an improvement over other topic-modeling approaches. Furthermore, our results support the hypothesis that subtle differences in language can be detected in narrative speech, even at the very early stages of cognitive decline, when scores on screening tools such as the Mini-Mental State Exam are still in the “normal” range.},
	journal      = {Computer Speech and Language},
	author       = {Fraser, Kathleen and Lundholm Fors, Kristina and Kokkinakis, Dimitrios},
	year         = {2019},
	volume       = {53},
	pages        = {121--139},
}

@inProceedings{lundholmfors-etal-2018-automated-263790,
	title        = {Automated Syntactic Analysis of Language Abilities in Persons with Mild and Subjective Cognitive Impairment},
	abstract     = {In this work we analyze the syntactic complexity of transcribed picture descriptions using a variety of automated syntactic features, and investigate the features’ predictive power in classifying narratives from people with subjective and mild cognitive impairment and healthy controls. Our results indicate that while there are no statistically significant differences, syntactic features can still be moderately successful at distinguishing the participant groups when used in a machine learning framework.},
	booktitle    = {Building continents of knowledge in oceans of data : the future of co-created eHealth: proceedings of MIE2018, 24-26 April 2018, Gothenburg, Sweden},
	editor       = {Adrien Ugon and Daniel Karlsson and Gunnar O. Klein and Anne Moen.},
	author       = {Lundholm Fors, Kristina and Fraser, Kathleen and Kokkinakis, Dimitrios},
	year         = {2018},
	publisher    = {IOS Press},
	address      = {Amsterdam},
	ISBN         = {978-1-61499-851-8},
}

@inProceedings{themistocleous-etal-2018-effects-270215,
	title        = {Effects of Mild Cognitive Impairment on vowel duration
},
	abstract     = {Mild cognitive impairment (MCI) is a neurological condition, which is characterized
by a noticeable decline of cognitive abilities, including communicative and linguistic
skills. In this study, we have measured the duration of vowels produced in a reading
task by 55 speakers— 30 healthy controls and 25 MCI—. The main results showed
that MCI speakers differed significantly from HC in vowel duration as MCI speakers
produced overall longer vowels. Also, we found that gender effects on vowel duration
were different in MCI and HC. One significant aspect of this finding is that they highlight
the contribution of vowel acoustic features as markers of MCI.},
	booktitle    = {Proceedings of the 9th Tutorial & Research Workshop on Experimental Linguistics, 28 - 30 August 2018, Paris, France},
	editor       = {Antonis Botinis},
	author       = {Themistocleous, Charalambos and Kokkinakis, Dimitrios and Eckerström, Marie and Fraser, Kathleen and Lundholm Fors, Kristina},
	year         = {2018},
	ISBN         = {978-960-466-162-6 },
}

@inProceedings{lundholmfors-etal-2018-voice-264400,
	title        = {Eye-voice span in adults with mild cognitive impairment (MCI) and healthy controls. },
	abstract     = {Objectives: This study is part of a larger project focused on developing new techniques for identification of early linguistic and extra-linguistic signs of cognitive impairment, with the overall goal of identifying dementia in the preclinical stage. In a previous study, we found that eye movements during reading can be used to distinguish between subjects with mild cognitive impairment (MCI) and healthy controls with up to 86% accuracy. In this study, we are investigating the process of reading aloud, by exploring the eye-voice span in subjects with and without cognitive impairment. The aim of the study is to identify differences in the reading processes and evaluate whether these differences can be used to discriminate between the two groups.
Methods: The eye-voice span is a measurement of the temporal and spatial organization between the eye and the voice, and is affected by for example working memory and automaticity, but also by the familiarity and length of words. In previous work, differences between eye movements when reading in healthy controls and subjects with cognitive impairments have been identified, and it has been shown that subjects with Alzheimer’s disease show impairments when reading aloud, specifically with regards to speech and articulation rate.
Results: We present a quantitative and qualitative analysis of the reading process in the subjects, focusing both on general measures of eye-voice span, but also specifically on instances of hesitation and mistakes in the speech, and the correlated eye movements.
Conclusions/Take home message: Early detection of dementia is important for a number of reasons, such as giving the person access to interventions and medications, and allowing the individual and families time to prepare. By expanding the knowledge about reading processes in subjects with MCI, we are adding to the potential of using reading analysis as an avenue of detecting early signs of dementia.},
	booktitle    = {Book of Abstracts 10th CPLOL Congress 10-12 May 2018, Cascais, Portugal / editor :  Trinite, Baiba },
	author       = {Lundholm Fors, Kristina and Fraser, Kathleen and Kokkinakis, Dimitrios},
	year         = {2018},
}

@inProceedings{kokkinakis-etal-2018-textforskning-265113,
	title        = {Kan textforskning bidra till tidigare och säkrare demensdiagnostik?},
	abstract     = {Tidigare forskning har visat att subtila språkstörningar kan finnas vid de tidigaste förstadierna till demens, flera år innan en klinisk diagnos kan ställas. Inom ramen för projektet ”Språkliga och extra-lingvistiska parametrar för tidig upptäckt av kognitiv svikt” (finansierat av Riksbankens Jubileumsutlysning, 2016-19) undersöker vi med hjälp av språkteknologi och språkanalysstudier hur dessa språkstörningar yttrar sig. Kan språkteknologi användas för att upptäcka dessa tidiga språkrelaterade symtom och därmed bidra med nyanserad, komplementär och användbar kunskap? Kan användning av språkteknologi särskilja personer med de allra tidigaste kognitiva avvikelserna från personer med mer godartad, åldersrelaterad kognitiv svikt? Vilka språkliga förmågor drabbas? Hur yttrar sig dessa förändringar och vilka slags empiriska material finns att tillgå? Dessa är några av de frågor vi söker svar på. Vi gör inspelningar som vi analyserar för att kunna ta fram ny kunskap om subtila språkliga kännetecken som kan föregå demensutveckling. Denna kunskap kan användas för att eventuellt kunna förutsäga vilka individer som befinner sig i riskzonen för att utveckla demens, och kan vara användbar som komplementerande beslutsunderlag till domänexperter. Vi utvinner, analyserar och undersöker om det finns samband mellan olika språkrelaterade parametrar från spontan talinteraktion, transkriptioner men även ögonrörelser och neuropsykologiska tester från personer med subjektiv eller lindrig kognitiv nedsättning och friska kontrollpersoner. Många gånger är det svårt att avgöra huruvida lindriga kognitiva symtom är en del av det normala åldrandet eller början på en neurodegenerativ process. Vi förväntar oss inte heller att varje enskild person med kognitiv nedsättning kommer att uttrycka sig eller läsa på samma sätt utan snarare att dessa personer tidigt i sjukdomsförloppet kommer att börja uppvisa olika slags avvikande läsmönster, eller göra fonologiska, lexikala, syntaktiska eller semantiska fel. I studien utvecklar vi verktyg för att automatiskt hitta dessa avvikelser, och målet är att detta sedan ska kunna användas som komplement till tidig diagnostik samt som prognostiskt eller screeningverktyg. Deltagarna i vår studie har rekryterats från en pågående longitudinell studie, ”Demens i Tidigt Skede”, (eng. ”The Gothenburg MCI study”) på Minnesmottagningen i Göteborg, och vårt projekt har godkänts av den lokala etiknämnden. Alla deltagare i studien (kontrollgruppen [HC], personer med subjektiv kognitiv nedsättning [SCI] och personer med mild kognitiv nedsättning [MCI]) har genomgått baslinjeundersökning och gett informerat skriftligt samtycke (demografisk information finns i tabell 1). Vårt projekt är f.n. pågående och vi kommer presentera resultat baserade på inspelningstillfälle nr ett (aug. 2016-mars 2017). En ny inspelningsomgång, med samma deltagare, började i februari 2018 och förväntas vara avslutat i december 2018. Under presentationen kommer vi ge exempel på olika tal-, text- och ögonrörelseanalyser vi har genomfört och diskutera metodval och resultat baserade på studiens första fas. Vi kommer vidare ge en kort inblick i den nya, pågående inspelningsomgången och de nya testmoment vi använder. Vi vill med vårt arbete visa hur språkteknologisk analys kan bidra till att utöka vår kunskap inom området så att den kan vara användbar för tidig diagnostik och optimal omvårdnad. Enligt Socialstyrelsen (2017) finns det i Sverige över 160 000 personer med någon demenssjukdom. Våra resultat kan ha en betydelse för vårdpersonal som snabbare vill diagnostisera och identifiera individer med olika former av kognitiv funktionsnedsättning innan allvarliga symtom blir påtagliga. Utvecklingsmöjligheterna är många: nya eller förbättrade kognitiva screeningtester som skulle kunna användas inom primär- och specialistvården, samt utveckling och tillämpning av insatser som kan påverka beteendemönster och träna upp individens kommunikativa förmåga, kan på sikt leda till positiva konsekvenser som minskade vårdköer samt effektivare behandling avseende kostnader och behandlingsutfall.},
	booktitle    = {Forum för textforskning 13 , Lund 7 – 8 juni 2018},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Eckerström, Marie and Themistocleous, Charalambos},
	year         = {2018},
}

@inProceedings{kokkinakis-etal-2018-swedish-262851,
	title        = {A Swedish Cookie-Theft Corpus},
	abstract     = {Language disturbances can be a diagnostic marker for neurodegenerative diseases, such as Alzheimer’s disease, at earlier stages, and connected speech analysis provides a non-invasive and easy-to-assess measure for determining aspects of the severity of language impairment. In this paper we focus on the development of a corpus consisting of audio recordings of picture descriptions of the Cookie-theft, produced by Swedish speakers, and accompanying transcriptions. The speech elicitation procedure provides an established method of obtaining highly constrained samples of connected speech that can allow us to study the intricate interactions between various linguistic levels and cognition. We chose the Cookie-theft picture since it is a standardized test that has been used in various studies in the past, and therefore comparisons can be made based on previous results. This type of picture description task might be useful for detecting subtle language deficits in patients with subjective and mild cognitive impairment. The resulting corpus is a new, rich and multi-faceted resource for the investigation of linguistic characteristics of connected speech and a unique data set that provides a rich resource for (future) research and experimentation in many areas, and of language impairment in particular. The information in the corpus can also be combined and correlated with other collected data about the speakers, such as neuropsychological tests, imaging and brain physiology markers and cerebrospinal fluid markers.},
	booktitle    = {LREC 2018, 11th edition of the Language Resources and Evaluation Conference, 7-12 May 2018, Miyazaki (Japan) / Editors:  Nicoletta Calzolari (Conference chair), Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Fraser, Kathleen and Nordlund, Arto},
	year         = {2018},
	publisher    = {European Language Resources Association},
	ISBN         = {979-10-95546-00-9},
}

@inProceedings{fraser-etal-2017-analysis-257840,
	title        = {An analysis of eye-movements during reading for the detection of mild cognitive impairment},
	abstract     = {We present a machine learning analysis of eye-tracking data for the detection of mild cognitive impairment, a decline in cognitive abilities that is associated with an increased risk of developing dementia. We compare two experimental configurations (reading aloud versus reading silently), as
well as two methods of combining information from the two trials (concatenation and merging). Additionally, we annotate the words being read with information about their frequency and syntactic category, and use these annotations to generate new features. Ultimately, we are able to distinguish between participants with and without cognitive impairment with up to 86% accuracy.},
	booktitle    = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. September 9-11, 2017 Copenhagen, Denmark / Editors Martha Palmer, Rebecca Hwa, Sebastian Riedel   },
	author       = {Fraser, Kathleen and Lundholm Fors, Kristina and Kokkinakis, Dimitrios and Nordlund, Arto},
	year         = {2017},
	publisher    = {Association for Computational Linguistics },
	ISBN         = {978-1-945626-83-8},
}

@inProceedings{breitholtz-etal-2010-multi-129279,
	title        = {A Multi-Dimensional Study of Cognitive Load in Dialogue},
	booktitle    = {NorDIsCo, Aalborg, 17th - 19th November 2010 },
	author       = {Breitholtz, Ellen and Ericsson, Stina and Lundholm Fors, Kristina and Villing, Jessica},
	year         = {2010},
}

@inProceedings{bjorkner-etal-2017-voice-256522,
	title        = {Voice acoustic parameters for detecting signs of early cognitive impairment},
	abstract     = {Aiding the detection of very early cognitive impairment in Alzheimer's disease (AD) and assessing the disease progression are essential foundations for effective psychological assessment, diagnosis and planning. Efficient tools for routine dementia screening in primary health care, particularly non-invasive and cost-effective methods, are desirable. The aim of this study is to find out if voice acoustic analysis can be a useful tool for detecting signs of early cognitive impairment.},
	booktitle    = {PEVOC (PanEuropean Voice Conference) 12, August 30th - September 1st 2017, Ghent, Belgium},
	author       = {Björkner, Eva and Lundholm Fors, Kristina and Kokkinakis, Dimitrios and Nordlund, Arto},
	year         = {2017},
}

@inProceedings{kokkinakis-etal-2017-data-256955,
	title        = {Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia},
	abstract     = {Cognitive and mental deterioration, such as difficulties with memory and language, are some of the typical phenotypes for most neurodegenerative diseases including Alzheimer’s disease and other dementia forms. This paper describes the first phases of a project that aims at collecting various types of cognitive data, acquired from human subjects in order to study relationships among linguistic and extra-linguistic observations. The project’s aim is to identify, extract, process, correlate, evaluate, and disseminate various linguistic phenotypes and measurements and thus contribute with complementary knowledge in early diagnosis, monitor progression, or predict individuals at risk. In the near future, automatic analysis of these data will be used to extract various types of features for training, testing and evaluating automatic classifiers that could be used to differentiate individuals with mild symptoms of cognitive impairment from healthy, age-matched controls and identify possible indicators for the early detection of mild forms of cognitive impairment. Features will be extracted from audio recordings (speech signal), the transcription of the audio signals (text) and the raw eye-tracking data.},
	booktitle    = {Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Björkner, Eva and Nordlund, Arto},
	year         = {2017},
	publisher    = {Linköping University Electronic Press, Linköpings universitet},
	address      = {Linköping},
	ISBN         = {978-91-7685-601-7},
}

@inProceedings{kokkinakis-etal-2016-data-243069,
	title        = {Data Resource Acquisition from People at Various Stages of Cognitive Decline – Design and Exploration Considerations},
	abstract     = {In this paper we are introducing work in progress towards the development of an infrastructure (i.e., design, methodology, creation and description) of linguistic and extra-linguistic data samples acquired from people diagnosed with subjective or mild cognitive impairment and healthy, age-matched controls. The data we are currently collecting consists of various types of modalities; i.e. audio-recorded spoken language samples; transcripts of the audio recordings (text) and eye tracking measurements. The integration of the extra-linguistic information with the linguistic phenotypes and measurements elicited from audio and text, will be used to extract, evaluate and model features to be used in machine learning experiments. In these experiments, classification models that will be trained, that will be able to learn from the whole or a subset of the data to make predictions on new data in order to test how well a differentiation between the aforementioned groups can be made. Features will be also correlated with measured outcomes from e.g. language-related scores, such as word fluency, in order to investigate whether there are relationships between various variables.},
	booktitle    = {The Seventh International Workshop on Health Text Mining and Information Analysis (Louhi). November 5, 2016, Austin, Texas, USA},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Nordlund, Arto},
	year         = {2016},
}

@inProceedings{lundholmfors-breitholtz-2016-mocking-240344,
	title        = {Are you mocking me or are you laughing with me?},
	booktitle    = { SEMDIAL 2016, JerSem, Proceedings of the 20th Workshop on the Semantics and Pragmatics of Dialogue, 16-18 July 2016 Rutgers, New Brunswick, NJ, USA /  Julie Hunter, Mandy Simons, and Matthew Stone (eds.)},
	author       = {Lundholm Fors, Kristina and Breitholtz, Ellen},
	year         = {2016},
}

@inProceedings{kokkinakis-etal-2016-specifications-243183,
	title        = {Specifications and Methodology for Language-Related Data Acquisition and Analysis in the Domain of Dementia Diagnostics},
	abstract     = {This paper outlines the initial stages of a project that aims to build and use a corpus with data samples acquired from people diagnosed with subjective or mild cognitive impairment and healthy, age-matched controls. The data we are currently collecting consists of audio-recorded spoken language samples; transcripts of the audio recordings and eye tracking measurements. From these data we plan to extract, evaluate and model features to be used for learning classification models in order to test how well a differentiation between the aforementioned subject groups can be made. Features will be also correlated with outcomes from e.g. other language-related scores, such as word fluency, in order to investigate whether there are relationships between various variables.},
	booktitle    = { The Sixth Swedish Language Technology Conference (SLTC) Umeå University, 17-18 November, 2016},
	author       = {Kokkinakis, Dimitrios and Lundholm Fors, Kristina and Björkner, Eva and Nordlund, Arto},
	year         = {2016},
}

@book{lundholmfors-2015-production-225015,
	title        = {Production and Perception of Pauses in Speech},
	abstract     = {Silences can make or break the conversation: if two persons involved in a conversation have different ideas about the typical length of pauses, they will face problems with turn taking. Pauses occur in conversation for a number of reasons, for example for breathing, thinking, word-searching and turn taking management. In this dissertation, we explore the production and perception of pauses in speech. Our aim consists of three main parts: to describe and analyse the production of pauses, to investigate the perception of pauses, and to examine the role of pauses in turn-taking. Our hypothesis is that pauses fill varying functions, and that these functions depend on the context of the pauses. We believe that the duration of pauses may be linked to the pause type, and that we adapt the our pause lengths to the persons we are speaking to. Further, we suggest that pauses occur regularly throughout dialogues. We also hypothesise that the duration of pauses in speech affect the processing of speech. Pauses are tied to the process of turn taking, and as we learn more about the nature of pauses we may also be able to further develop our understanding of the process of turn holding and turn yielding. We will also be able to use the information about pause production and perception when modelling turn taking in dialogue systems. Our results show that pause lengths vary greatly across speakers, pause types and dialogues. Pauses tend to be entrained by speakers involved in dialogues, and pauses occur regularly throughout conversations. We also found evidence that pauses have a positive impact on memorising spoken utterances. While speakers adapt their pause lengths to the other speaker in the conversation, they are inclined to keep a consistent ratio between pause types, and this is not dependent on the conversational partner. While it is interesting to look at pauses separately, we need to put them into context to really understand their functions. To highlight the role of pauses in conversation, we proposed an updated turn taking model, where the results from our studies are integrated.},
	author       = {Lundholm Fors, Kristina},
	year         = {2015},
	publisher    = {University of Gothenburg},
	address      = {Göteborg},
}

@inProceedings{lundholmfors-2012-temporal-163151,
	title        = {The temporal relationship between feedback and pauses: a pilot study.},
	abstract     = {In this pilot study we investigated the temporal relationship between pauses and feedback. We found that the
majority of feedback items occur in the proximity of trppauses (pauses that occur at a trp, within a speaker’s turn),
but also that most intraturn pauses do not coincide with
feedback units. This suggests that when modeling feedback in human-computer interaction, a method to identify
trp-pauses will also provide suitable places for feedback.},
	booktitle    = {Interdisciplinary Workshop on Feedback Behaviors in Dialog (an Interspeech 2012 satellite event)},
	author       = {Lundholm Fors, Kristina},
	year         = {2012},
}

@inProceedings{lundholmfors-2012-synchrony-163150,
	title        = {Synchrony and convergence of pause lengths in spontaneous conversation},
	booktitle    = {ISICS 2012: International Symposium on Imitation and Convergence in Speech},
	author       = {Lundholm Fors, Kristina},
	year         = {2012},
}

@inProceedings{lundholmfors-2011-pause-146574,
	title        = {Pause length variations within and between speakers over time},
	abstract     = {In the current study, intra-turn pause variation has been investigated within and between
speakers in dialogues. Results show that there
is a tendency for different speakers to prefer
different pause locations within turns. There
was further a significant correlation in the majority of the dialogues between how the median lengths of pauses varied for the speakers
over the course of the dialogues. The conclusion that can be drawn from this study is that
speakers seem to show individual patterns as
to where they prefer to pause within turns, but
pause length variations tend to be correlated
between speakers in the same dialogue.},
	booktitle    = {SemDial 2011 (Los Angelogue): Proceedings of the 15th workshop on Semantics and Pragmatics of Dialogue.},
	author       = {Lundholm Fors, Kristina},
	year         = {2011},
	pages        = {198--199},
}

@article{lundholmfors-villing-2011-reducing-146576,
	title        = {Reducing cognitive load in in-vehicle dialogue system interaction},
	abstract     = {In-vehicle dialogue systems need to be able to
adapt to the cognitive load of the user, and,
when possible, reduce cognitive load. To accomplish this, we need to know how humans
act while driving and talking to a passenger,
and find out if there are dialogue strategies
that can be used to minimize cognitive load.
In this study, we have analyzed human-human
in-vehicle dialogues, focusing on pauses and
adjacency pairs. Our results show that when
the driver is experiencing high cognitive load,
the passenger’s median pause times increase.
We also found that, when switching to another
domain and/or topic, both driver and passenger try to avoid interrupting an adjacency pair.
This suggests that a dialogue system could
help lower the user’s cognitive load by increasing pause lengths within turns, and plan
system utterances in order to avoid switching
task within an adjacency pair.},
	journal      = {SemDial 2011: Proceedings of the 15th Workshop on the Semantics and Pragmatics of Dialogue},
	author       = {Lundholm Fors, Kristina and Villing, Jessica},
	year         = {2011},
	pages        = {55--62},
}

@article{lundholmfors-2011-investigation-141540,
	title        = {An investigation of intra-turn pauses in spontaneous speech},
	abstract     = {In this study, pauses within speakers’ turns are described and analysed. Tentative results show that different pauses within a speaker’s turn might differ in length. Pause length variations over time in dialogues were investigated, and in 5 out of 6 dialogues, a statistically significant correlation was found between the speakers’ variations in pause length.},
	journal      = {Proceedings from Fonetik 2011: TMH-QPSR},
	author       = {Lundholm Fors, Kristina},
	year         = {2011},
	volume       = {51},
	pages        = {65--68},
}

@inProceedings{lundholmfors-2011-categorization-140918,
	title        = {Categorization of pauses in conversational speech},
	abstract     = {Pauses are often divided into pauses between turns and pauses within
turns; that is pauses where speaker change takes place, and pauses
where the same speaker speaks before and after the pause. While this
may be one way to categorize pauses, a further categorization will here
be suggested and backed up by data.
Within turns, there are two possible pause locations: a pause may
occur at a possible transition relevance place (TRP), or it can occur
within a syntactic unit. This suggests that when the pause occurs
at a TRP, the speakers negotiate whether the current speaker shall
continue speaking, or if there will be a turn change. When the speaker
pauses within a syntactic unit, it is more clear that the speaker that
spoke before the pause will continue after the pause. In analogy with
this, at a turn change where no speaker has been nominated, speakers
need to negotiate who will take the turn. When a speaker has been
nominated by the previous speaker, the pause at the turn change does
not include “turn negotiation.”
When investigating pause lengths and variance, the pause types
that do not include turn negotiation show clear similarities, as do the
pauses that do include turn negotiation. It is therefore possible to
conclude that when only dividing pauses into occurring between and
within turns, some of the features that characterize different pause
types are lost.},
	booktitle    = {Speaking of prosody: A symposium in conjunction with the 60th birthday of Professor Merle Horne. Lund University, May 21 2011 },
	author       = {Lundholm Fors, Kristina},
	year         = {2011},
}

@article{antonsson-etal-2021-using-301490,
	title        = {Using a Discourse Task to Explore Semantic Ability in Persons With Cognitive Impairment.},
	abstract     = {This paper uses a discourse task to explore aspects of semantic production in persons with various degree of cognitive impairment and healthy controls. The purpose of the study was to test if an in-depth semantic analysis of a cognitive-linguistic challenging discourse task could differentiate persons with a cognitive decline from those with a stable cognitive impairment. Both quantitative measures of semantic ability, using tests of oral lexical retrieval, and qualitative analysis of a narrative were used to detect semantic difficulties. Besides group comparisons a classification experiment was performed to investigate if the discourse features could be used to improve classification of the participants who had a stable cognitive impairment from those who had cognitively declined. In sum, both types of assessment methods captured difficulties between the groups, but tests of oral lexical retrieval most successfully differentiated between the cognitively stable and the cognitively declined group. Discourse features improved classification accuracy and the best combination of features discriminated between participants with a stable cognitive impairment and those who had cognitively declined with an area under the curve (AUC) of 0.93.},
	journal      = {Frontiers in aging neuroscience},
	author       = {Antonsson, Malin and Lundholm Fors, Kristina and Eckerström, Marie and Kokkinakis, Dimitrios},
	year         = {2021},
	volume       = {12},
}

@inProceedings{themistocleous-etal-2020-improving-305222,
	title        = {Improving the Diagnosis of Mild Cognitive Impairment in elderly individuals using a multifactorial automatic analysis of voice quality and prosody.},
	abstract     = {http://demo.spraakdata.gu.se/svedk/pbl/AEC-30-Paper.JPG},
	booktitle    = {30th Alzheimer Europe Conference #30AEC -- virtual conference },
	author       = {Themistocleous, Charalambos and Eckerström, Marie and Lundholm Fors, Kristina and Kokkinakis, Dimitrios},
	year         = {2020},
}