Dialogue analysis

Language oriented qualitative research uses themes, scripts, narratives, or conversations to derive inductive inferences about observed phenomenon. Parents of children with developmental disabilities report difficulty in finding willing, nonjudgmental audiences for the stories they want to tell. The analysis of themes, scripts, narratives or conversations they make is the chosen objective of this study. A purposive sample of 4 parents formed a part of this study involving unstructured interviews on identified topics.Data collection involved immediate noting and transcription of the professional-parent conversations. The corpus of verbatim experiential narratives was coded and classified between multiple examiners to ensure reliability. Results show the emergence of four themes(i) search for diagnosis; (ii) diagnostic disclosure; (iii) expectations from therapy; and, (iv) home situation. They state concern about their child's safety and future security, express grief over the loss of a "dream child," convey perplexity, eagerness to know, worries on what others may think, abhorjargon used by professionals, have unclear expectations, and patterns of help-seeking.The findings are discussed along with their implications for organizing periodic parent-professional interactive support programs. Language oriented qualitative research attempts to gather non-numerical data. It typically seeks to unravel meanings, concepts definitions, characteristics, metaphors, symbols, and descriptions of things. It is based on grounded theory. It inquires the why and how of a phenomenon rather than how much or how often. Their approach is inductive (specific to

It has been observed that viewers perceive scripted television dialogue as similar or identical to unscripted conversation. However, it has also been noted that there are a vast number of features in which scripted television dialogue differs from unscripted conversation. In this paper, I suggest that viewers are able to correctly identify both types of dialogue and thus do not identify scripted dialogue as unscripted dialogue. For this research, a small-scale pilot study was set up to test the hypothesis. The experiment also attempted to discover what features viewers pick up on and whether these coincide with the list of features signifying scripted television dialogue. Based on the list of features from the literature, the hypothesis was that viewers are not better at correctly identifying unscripted conversation than they are at correctly identifying scripted dialogue. Statistical tests indicated that there was no significance between the number of participants that correctly identified unscripted conversation and the number of participants that correctly identified scripted television dialogue. The qualitative section showed that participants identify similar features as those provided by the literature, but also pay attention to linguistically unrelated issues such as background sounds and sound quality. Finally, even though this research is a pilot-study, some advice to scriptwriters is provided.

Over the past decade, the paradigm of the World Wide Web has shifted from static web pages towards participatory and collaborative content production. The main properties of this user generated content are a low publication threshold and little or no editorial control. While this has improved the variety and timeliness of the available information, it causes an even higher variance in quality than the already heterogeneous quality of traditional web content. Wikipedia is the prime example for a successful, large-scale, collaboratively created resource that reflects the spirit of the open collaborative content creation paradigm.
Even though recent studies have confirmed that the overall quality of Wikipedia is high, there is still a wide gap that must be bridged before Wikipedia reaches the state of a reliable, citable source.

A key prerequisite to reaching this goal is a quality management strategy that can cope both with the massive scale of Wikipedia and its open and almost anarchic nature. This includes an efficient communication platform for work coordination among the collaborators as well as techniques for monitoring quality problems across the encyclopedia. This dissertation
shows how natural language processing approaches can be used to assist information quality management on a massive scale.

In the first part of this thesis, we establish the theoretical foundations for our work. We first introduce the relatively new concept of open online collaboration with a particular focus on collaborative writing and proceed with a detailed discussion of Wikipedia and its role as an encyclopedia, a community, an online collaboration platform, and a knowledge resource for language technology applications. We then proceed with the three main contributions of this thesis.

Even though there have been previous attempts to adapt existing information quality frameworks to Wikipedia, no quality model has yet incorporated writing quality as a central
factor. Since Wikipedia is not only a repository of mere facts but rather consists of full text articles, the writing quality of these articles has to be taken into consideration when judging article quality. As the first main contribution of this thesis, we therefore define a comprehensive article quality model that aims to consolidate both the quality of writing and the quality criteria defined in multiple Wikipedia guidelines and policies into a single model. The model comprises 23 dimensions segmented into the four layers of intrinsic quality, contextual quality, writing quality and organizational quality.

As a second main contribution, we present an approach for automatically identifying quality flaws in Wikipedia articles. Even though the general idea of quality detection has been introduced in previous work, we dissect the approach to find that the task is inherently prone to a topic bias which results in unrealistically high cross-validated evaluation results that do not reflect the classifier’s real performance on real world data.

We solve this problem with a novel data sampling approach based on the full article revision history that is able to avoid this bias. It furthermore allows us not only to identify flawed articles but also to find reliable counterexamples that do not exhibit the respective quality flaws. For automatically detecting quality flaws in unseen articles, we present FlawFinder, a modular system for supervised text classification. We evaluate the system on a novel corpus of Wikipedia articles with neutrality and style flaws. The results confirm the initial hypothesis that the reliable classifiers tend to exhibit a lower cross-validated performance than the biased ones but the scores more closely resemble their actual performance
in the wild.

As a third main contribution, we present an approach for automatically segmenting and tagging the user contributions on article Talk pages to improve the work coordination among Wikipedians. These unstructured discussion pages are not easy to navigate and information is likely to get lost over time in the discussion archives. By automatically identifying the quality problems that have been discussed in the past and the solutions that have been proposed, we can help users to make informed decisions in the future.

Our contribution in this area is threefold: (i) We describe a novel algorithm for segmenting the unstructured dialog on Wikipedia Talk pages using their revision history. In contrast to related work, which mainly relies on the rudimentary markup, this new algorithm can reliably extract meta data, such as the identity of a user, and is moreover able to handle discontinuous turns. (ii) We introduce a novel scheme for annotating the turns in article discussions with dialog act labels for capturing the coordination efforts of article improvement. The labels reflect the types of criticism discussed in a turn, for example missing information or inappropriate language, as well as any actions proposed for solving the quality problems. (iii) Based on this scheme, we created two automatically segmented and manually annotated discussion corpora extracted from the Simple English Wikipedia (SEWD) and the English Wikipedia (EWD). We evaluate how well text classification approaches can learn to assign the dialog act labels from our scheme to unseen discussion pages and achieve a cross-validated performance of F1 = 0.82 on the SEWD corpus while we obtain an average performance of F1 = 0.78 on the larger and more complex EWD corpus.

In this study, we investigate the distribution and properties of hesitation markers produced in task-oriented dialogues by Polish and German teenagers.  The materialcomes from a multimodal corpus which has been collected in the Polish-German bor-der area, in the cities of Słubice and Frankfurt (Oder).  The speakers took part in twokinds of dialogue tasks:  a collaborative and a competitive one.  We report that thenumber and durational variability of hesitation markers produced by the speakers areinfluenced by dialogue task type and language configuration.  We inspect aspects ofinterlocutor alignment using automatized annotation mining. A number of patterns ofalignment can be visually traced for the study material.  However, only few of them can be confirmed by tests as statistically significant.

We present an approach to automatic detection of Alzheimer’s type dementia based on characteristics of spontaneous spoken language dialogue consisting of interviews recorded in natural settings. The proposed method employs additive logistic regression on content-free features extracted from dialogical interaction to build a predictive model. The model training data consisted of dialogues between Alzheimer’s patients and interviewers and dialogues between patients with other health conditions and interviewers. Features analysed included speech rate, turn-taking patterns and other speech parameters. Despite relying solely on content-free features, our results are comparable to those of state-of-the-art methods that employ more complex lexical and syntactic features. While further investigation is needed, these promising results suggest that it is possible to design non-invasive and low-cost mental health monitoring tools for realistic everyday settings.

Over the past decade, the paradigm of the World Wide Web has shifted from static web pages towards participatory and collaborative content production. The main properties of this user generated content are a low publication threshold and little or no editorial control. While this has improved the variety and timeliness of the available information, it causes an even higher variance in quality than the already heterogeneous quality of traditional web content. Wikipedia is the prime example for a successful, large-scale, collaboratively created resource that reflects the spirit of the open collaborative content creation paradigm. Even though recent studies have confirmed that the overall quality of Wikipedia is high, there is still a wide gap that must be bridged before Wikipedia reaches the state of a reliable, citable source. A key prerequisite to reaching this goal is a quality management strategy that can cope both with the massive scale of Wikipedia and its open and almost anarch...

Identity Aspects and Speech Analysis in Franz Xaver Kroetz's Drama " Mensch Meier " The paper is a study of Franz Xaver Kroetz's Mensch Meier dramatic scenes based on literary theory and sociolinguistics, combining the sociological approach and the methods of conversational analysis. It aims to show the ways in which the author represents social reality. To achieve this, it was established what features of language used in creating the fictional world were employed to characterize a member of the working class in his attempt to advance in society.

An approach to dialogue is presented that combines Conversational Analysis, the study of evaluation in discourse, and a critical interactionist perspective. The research concentrates on the changes that Venezuelan dialogue has undergone in the last ten years, beginning especially with President Hugo Chávez’s government (1999). The focus of the analysis is on conflictive moments and the social actors that participate in the macro-dialogue. Dialogue is examined along four broad dimensions: the dialogue between presidents and the Venezuelan people at the moment of inauguration; the dialogue between President Chávez and his followers and opponents; the polarization between opponents and followers who evaluate the exchanged insults during the most conflictive moments; and the conflictive dialogue extended to the international level.
Key words: Dialogue, political practice, conflict, evaluation, interaction, Venezuela

The present work is an exploratory study of the form and function of final rises in Polish task-oriented dialogues. Ten dialogue sessions were selected from the DiaGest2 corpus and analysed for the occurrence and realisation of phrase-final rises. They are tagged for dialogue act category and basic contextual properties (overlap, turn position) and analysed for the basic acoustic parameters. The results support and enhance findings of earlier works for the Polish language and, while showing some tendencies in terms of form-function correlation, they also confirm the complexity of intonational mechanisms in task-oriented dialogues.

Introduction:
Decreasing the incidence of Alzheimer’s disease (AD) is a global public health priority. Early detection of AD is an important requisite for the implementation of prevention strategies towards this goal. While it is plausible that patients at the early stages of AD may exhibit subtle behavioural signs of neurodegeneration, neuropsychological testing seems unable to detect these signs in preclinical AD. Recent studies indicate that spontaneous speech data, which can be collected frequently and naturally, provide good predictors for AD detection in cohorts with a clinical diagnosis. The potential of models based on such data for detecting preclinical AD remains unknown.

Methods and analysis:
The PREVENT-Elicitation of Dialogues (PREVENT-ED) study builds on the PREVENT Dementia project to investigate whether early behavioural signs of AD may be detected through dialogue interaction. Participants recruited through PREVENT, aged 40–59 at baseline, will be included in this study. We will use speech processing and machine learning methods to assess how well speech and visuospatial markers agree with neuropsychological, biomarker, clinical, lifestyle and genetic data from the PREVENT cohort.

Ethics and dissemination:
There are no expected risks or burdens to participants. The procedures are not invasive and do not raise significant ethical issues. We only approach healthy consenting adults and all participants will be informed that this is an exploratory study and therefore has no diagnostic aim. Confidentiality aspects such as data encryption and storage comply with the General Data Protection Regulation and with the requirements from sponsoring bodies and ethical committees. This study has been granted ethical approval by the London-Surrey Research Ethics Committee (REC reference No: 18/LO/0860), and by Caldicott and Information Governance (reference No: CRD18048). PREVENT-ED results will be published in peer-reviewed journals.

Recent studies on question generation identify the need for automatic discourse analysers. We evaluated the feasibility of integrating an available discourse analyser called HILDA for a specific question generation system called CODA; introduce an approach by extracting a discourse corpus from the CODA parallel corpus; and identified future work towards automatic discourse analysis in the domain of question generation.

An old text. Maybe it can somehow interest someone...
Many aspects of the constitutional theory about referendums can be treated in a linguistic theory if one considers referendums as a particular form of dialog in which the institutions and the voters are concerned. The dialogical structure of referendary consultations is analyzed here according to the transphrastic perspective proposed by Sorin Stati. As a result, each member of the couple "question-answer" which expresses the referendum turns out to have not only the functions of "question" and "assertion", respectively, but also other performative functions. The  two text sequences are in this respect equivalent to - and substitutable by - non-linguistic acts.

A Group decision-making necessarily involves communication. Deciding is an individual cognitive act and a group speech act. Thus, analyzing a proposition proffered/assumed/attributed to an entity (individual or collective) is in the scope of communicative rationality. It is quite reasonable to consider that rational agency patterns applied to individuals (centrally, making a doxastic decision towards p, as knowing, believing, assuming it as true or false; entertaining propositions, having justification) are valid to group agency. We can approach a group as an entity governed by the same patterns of rationality applied to humans individually, since such groups are formed and represented by individuals. However, we assume here that with respect to cognitive-communicative human behavior some of these considerations of individual agency could not be used to provide an adequate framework of collective agency, since the latter is governed by specific principles, presented as follows: 1) We can describe internal group status (recognition) and external group status (attributions). Concerning the first one, we assume the existence of a set of conscious general relations that link individuals under the realm of an agency and allow them to qualify themselves as a specific entity in the world. Concerning the second one, we assume that we can identify individuals or institutions as a collective agent and we can attach acts and content to them. Besides, we assume that communication is required for internal and external manifestability.

[Introduction/Motivation:]
Due to the severe incidence of dementia across the world, its care and prevention are increasingly demanded by public health, with a focus on early detection and improved caregiving. As language impairment is a common symptom of dementia and a good source of clinical information for its assessment, our research aims to characterise potentially disrupted communication patterns related to cognitive function and decline. Identifying such features will ultimately help us design assistive technologies able to automatically monitor cognitive status (i.e. adaptive interfaces, social robotics), in order to allow older people to live at home longer, and as independently as possible. In the present work, our hypothesis is that patients suffering from Alzheimer’s Disease (AD) will show identifiable patterns during dialogue interactions (i.e. disrupted turn-taking patterns, differences in speech rate).
[Methods:]
We employ spontaneous, conversational data gathered by the Carolina Conversations Collections to train a machine learning model to differentiate AD and non-AD patients. Here, we included 21 patients and 17 controls, over 65 years old. The data was pre-processed to generate vocalisation graphs (figure 1) and extract speech rate information. These and the diagnostic annotations (AD vs. non-AD) were used for the supervised learning training of the model. Then, this classifier was evaluated on its ability to predict such annotations (AD vs. non-AD), implementing 10-fold cross-validation.
[Results and Discussion:]
The classifier reached up to 83% accuracy, based on turn-taking patterns and speech rate. Precision, recall and 𝐹" scores were also calculated (figure 2). These are preliminary results of a research in progress, as we are currently pre-processing the rest of the dataset and will be trying different methods for dialogue analysis and natural language processing in the short term.
All in all, there are several linguistic parameters that are promising to be helpful in the assessment of cognitive functioning. Our approach does not rely on speech transcription content, but on speech- silence patterns and basic prosodic information extracted from spontaneous spoken dialogue. Still, it obtains levels of accuracy comparable to state-of-the-art systems that rely on more complex features. This opens the possibility of devising mental health monitoring methods which would be non-invasive and low-cost in terms of time and resources.
[Aknowledments:]
We acknowledge C. Pope and B. H. Davis, from the Medical University of South Carolina, host to the Carolina Conversation Collection. Our research is supported by the UK Medical Research Council.