| 1. |
- Kokkinakis, Dimitrios, 1965, et al.
(author)
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Query Logs as a Corpus.
- 2013
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In: Corpus Linguistics 2013 : abstract book. Lancaster: UCREL / edited by Andrew Hardie and Robbie Love.
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Conference paper (other academic/artistic)abstract
- This paper provides a detailed description of a large Swedish health-related query log corpus and explores means to derive useful statistics, their distributions and analytics from its content across several dimensions. Information acquisition from query logs can be useful for several purposes and potential types of users, such as terminologists, infodemiologists / epidemiologists, medical data and web analysts, specialists in NLP technologies such as information retrieval and text mining but also public officials in health and safety organizations.
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| 2. |
- Johansson, Richard, 1975, et al.
(author)
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Semantic Role Labeling with the Swedish FrameNet
- 2012
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In: Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12); Istanbul, Turkey; May 23-25. - 9782951740877 ; , s. 3697-3700
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Conference paper (peer-reviewed)abstract
- We present the first results on semantic role labeling using the Swedish FrameNet, which is a lexical resource currently in development. Several aspects of the task are investigated, including the selection of machine learning features, the effect of choice of syntactic parser, and the ability of the system to generalize to new frames and new genres. In addition, we evaluate two methods to make the role label classifier more robust: cross-frame generalization and cluster-based features. Although the small amount of training data limits the performance achievable at the moment, we reach promising results. In particular, the classifier that extracts the boundaries of arguments works well for new frames, which suggests that it already at this stage can be useful in a semi-automatic setting.
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| 3. |
- Kokkinakis, Dimitrios, 1965
(author)
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Shallow Features for Differentiating Disease-Treatment Relations using Supervised Learning, a pilot study
- 2009
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In: Proceedings of the 12th International Conference TSD (Text, Speech and Dialogue). Springer Verlag, LNCS/LNAI series.. ; 5729, s. 395-402
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Conference paper (other academic/artistic)abstract
- Clinical narratives provide an information rich, nearly unexplored corpus of evidential knowledge that is considered as a challenge for practitioners in the language technology field, particularly because of the nature of the texts (excessive use of terminology, abbreviations, orthographic term variation), the significant opportunities for clinical research that such material can provide and the potentially broad impact that clinical findings may have in every day life. It is therefore recognized that the capability to automatically extract key concepts and their relationships from such data will allow systems to properly understand the content and knowledge embedded in the free text which can be of great value for applications such as information extraction and question & answering. This paper gives a brief presentation of such textual data and its semantic annotation, and discuss the set of semantic relations that can be observed between diseases and treatments in the sample. The problem is then designed as a machine learning task in which the relations are tried to be learned in a supervised fashion, using pre-annotated data. The challenges designing the problem and empirical results are presented.
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| 4. |
- Borin, Lars, 1957, et al.
(author)
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Mining semantics for culturomics: towards a knowledge-based approach
- 2013
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In: 2013 ACM International Workshop on Mining Unstructured Big Data Using Natural Language Processing, UnstructureNLP 2013, Held at 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 28 October 2013 through 28 October 2013. - New York, NY, USA : ACM. - 9781450324151 ; , s. 3-10
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Conference paper (peer-reviewed)abstract
- The massive amounts of text data made available through the Google Books digitization project have inspired a new field of big-data textual research. Named culturomics, this field has attracted the attention of a growing number of scholars over recent years. However, initial studies based on these data have been criticized for not referring to relevant work in linguistics and language technology. This paper provides some ideas, thoughts and first steps towards a new culturomics initiative, based this time on Swedish data, which pursues a more knowledge-based approach than previous work in this emerging field. The amount of new Swedish text produced daily and older texts being digitized in cultural heritage projects grows at an accelerating rate. These volumes of text being available in digital form have grown far beyond the capacity of human readers, leaving automated semantic processing of the texts as the only realistic option for accessing and using the information contained in them. The aim of our recently initiated research program is to advance the state of the art in language technology resources and methods for semantic processing of Big Swedish text and focus on the theoretical and methodological advancement of the state of the art in extracting and correlating information from large volumes of Swedish text using a combination of knowledge-based and statistical methods.
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| 5. |
- Kokkinakis, Dimitrios, 1965, et al.
(author)
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HFST-SweNER . A New NER Resource for Swedish
- 2014
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In: Proceedings of the 9th edition of the Language Resources and Evaluation Conference (LREC), Reykjavik 26 - 31 May 2014.. - 9782951740884 ; , s. 2537-2543
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Conference paper (peer-reviewed)abstract
- Named entity recognition (NER) is a knowledge-intensive information extraction task that is used for recognizing textual mentions of entities that belong to a predefined set of categories, such as locations, organizations and time expressions. NER is a challenging, difficult, yet essential preprocessing technology for many natural language processing applications, and particularly crucial for language understanding. NER has been actively explored in academia and in industry especially during the last years due to the advent of social media data. This paper describes the conversion, modeling and adaptation of a Swedish NER system from a hybrid environment, with integrated functionality from various processing components, to the Helsinki Finite-State Transducer Technology (HFST) platform. This new HFST-based NER (HFST-SweNER) is a full-fledged open source implementation that supports a variety of generic named entity types and consists of multiple, reusable resource layers, e.g., various n-gram-based named entity lists (gazetteers).
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| 6. |
- Kokkinakis, Dimitrios, 1965
(author)
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Annotation of interpersonal relations in Swedish prose fiction.
- 2013
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In: Proceedings of the 3rd Workshop on Annotation of Corpora for Research in the Humanities (ACRH-3). Sofia, Bulgaria.. - 9789549170054 ; , s. 37-47
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Conference paper (peer-reviewed)abstract
- This paper describes the manual annotation of a small sample of Swedish 19th and 20th century prose fiction with interpersonal relations between characters in six literary works. An interpersonal relationship is an association between two or more people that may range in duration from brief to enduring. The annotation is guided by a named entity recognition step. Our goal is to get an in-depth understanding of the difficulties of such a task and elaborate a model that can be applied for similar annotation on a larger scale, both manually as well as automatically. The identification of interpersonal relations can, hopefully, aid the reader of a Swedish literary work to better understand its content and plot, and get a bird’s eye view on the landscape of the core story. Our aim is to use such annotations in a hybrid context, i.e., using machine learning and rule-based methods, which, in conjunction with named entity recognition, can provide the necessary infrastructure for creating detailed biographical sketches and extracting facts for various named entities which can be exploited in various possible ways by Natural Language Processing (NLP) technologies such as summarization, question answering, as well as visual analytic techniques.
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| 7. |
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| 8. |
- Allvin, H., et al.
(author)
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Characteristics and Analysis of Finnish and Swedish Clinical Intensive Care Nursing Narratives
- 2010
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In: Proceedings of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents. ; , s. 53 - 60
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Conference paper (peer-reviewed)abstract
- We present a comparative study of Finnish and Swedish free-text nursing narratives from intensive care. Although the two languages are linguistically very dissimilar, our hypothesis is that there are similarities that are important and interesting from a language technology point of view. This may have implications when building tools to support producing and using health care documentation. We perform a comparative qualitative analysis based on structure and content, as well as a comparative quantitative analysis on Finnish and Swedish Intensive Care Unit (ICU) nursing narratives. Our findings are that ICU nursing narratives in Finland and Sweden have many properties in common, but that many of these are challenging when it comes to developing language technology tools.
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| 9. |
- Beccaria, Federica, et al.
(author)
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Extraction and Analysis of Acoustic Features from Italian-Speaking Children with Autism Spectrum Disorder
- 2023
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In: The 22nd International Society for Autism Research (INSAR).
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Conference paper (other academic/artistic)abstract
- Background: The persistent difficulties in social interaction and communication that characterize Autism Spectrum Disorder can be accessed by investigating the quality of language. Indeed, these deficits involve the presence of anomalies in speech production and understanding, which find an expression at the acoustic and prosodic levels of linguistic analysis. Objectives: The main aim of this work is to propose a speech pipeline for the extraction of Italian speech biomarkers typical of ASD by conducting an acoustic and phonological analysis. Moreover, we will highlight the strengths and difficulties of this kind of investigation introducing new topics for further research. Methods: The poster will present the analysis of a speech corpus of 14 Italian-speaking children with ASD and 14 controls (C). The corpus is demographically balanced (age 6-10, 8;1 ± 1;3. Sex: 3F, 11 M) and homogeneous at the diatopic level (origin: Prato, Pistoia, Florence). First, we extracted the acoustic features by using eGeMAPS (openSMILE; Eyben et al., 2015), specifically ideated for the study of impaired speech. Then, we implemented the Mann-Whitney U-test to select the features with the most statistically significant distance in the production of the two groups. Secondly, we conducted a parallel extraction regarding the pitch (F0 mean and standard deviation). We propose this additional analysis because pitch varies according to some demographic traits of the speaker (sex, age, height) and the literature presents opposite trends. For this task, we used Praat to have more flexibility in the manipulation of the extraction. We set the F0 range between 70 and 400 Hz (Patel et al., 2020). Finally, we conducted a comparison between the results of the two methods excluding female participants to verify if the trend of pitch changes when the participants are not mixed. Results: Table 1 shows the features selected between the ones extracted. They are related to prosody, quality of voice, loudness, and spectral distribution. Jitter, shimmer and HNR are usually investigated together to describe the emotional prosody and the quality of voice. The same trend found on our corpus is recorded in previous studies on languages other than Italian (Bone et al. 2015; Kissine & Geelhand 2019). Moreover, spectral flux is usually investigated together with shimmer and jitter to describe speech impairments (Haider et al., 2019). Nevertheless, if we consider the studies related to autistic speech, there are few that describe this feature because of the different methodologies used during the extraction. Finally, the values of pitch extracted by eGeMAPS and Praat show the same trend. It is higher in ASD than in controls, both if we considered the corpus mixed and the one with only the male speakers. However, the pitch does not show a statistically significant difference between the two groups (Table 2). Conclusions: These results, although preliminary, seem to confirm the presence of phonetic alterations of speech associated with the disorder. Further studies could improve the accuracy of the pipeline proposed by doing a qualitative analysis of the results and considering other linguistic and paralinguistic domains (e.g., morphological, pragmatic, and gestural analysis).
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| 10. |
- Belmonte, Marica, et al.
(author)
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Automatic Detection of Rhythmic Features in Pathological Speech of MCI and Dementia Patients
- 2024
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In: RaPID-5: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments. - : European Language Resources Association (ELRA). - 9782493814111
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Conference paper (peer-reviewed)abstract
- The presence of linguistic alterations represents one of the prodromal signs of cognitive decline associated with dementia. In recent years, a growing body of work has been devoted to the development of algorithms for the automatic linguistic analysis of both oral and written texts, with diagnostic purposes. The extraction of Digital Linguistic Biomarkers from patients' verbal productions can indeed provide a rapid, ecological, and cost-effective system for large-scale screening of the pathology. This article contributes to the ongoing research in the field by exploring a traditionally less studied aspect of language in dementia, namely the rhythmic characteristics of speech. In particular, the paper focuses on the automatic detection of rhythmic features in Italian connected speech. A landmark-based system was developed and evaluated to segment the speech flow into vocalic and consonantal intervals and to calculate several rhythmic metrics. Additionally, the reliability of these metrics in identifying MCI and dementia patients was tested.
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