Interpersonal Functions of Doctor-Patient Conversations

As an indispensable part of medical practice.doctor-patient conversation is drawing more and more attention in the field of sociology,psychology and linguistics.Little attention,however,has been paid to the interpersonal aspect of the conversation between doctors and patients,which is regarded as one of the most complex interpersonal relationships.Being dominant in the interaction,doctors'words,mainly in the form of questions,deserve more studies,especially for the interpersonal functions delivered.This study mainly focuses on this aspect.

Cluster Analysis Based on Contextual Features Extraction for Conversational Corpus

Cluster analysis related to computational linguistics seldom concerned with Pragmatics level. Features of corpus on Pragmatics level related to specific situations, including backgrounds, titles and habits. To improve the accuracy of clustering for conversations collected from international students in Tsinghua University, it required contextual features. Here, we collected four-hundred conversations as a corpus and built it to Vector Space Model. With the Oxford-Duden Dictionary and other methods we modified the model and concluded into three groups. We testified our hypothesis through self-organizing map neural network. The result suggested that the modified model had a better outcome.

Lexical characteristics of dialogue acts in the Switchboard Corpus of telephone conversations

This paper describes a corpus-based investigation of dialogue acts.In particular,it attempts to answer questions about the empirical distribution of dialogue acts in a publicly accessible corpus of transcribed conversations and degrees of lexical similarity of dialogue acts.The research will not only lend itself to a deeper understanding of the lexical realisation of dialogue acts as communicative functions but also contribute towards dialogue act recognition.The Switchboard Dialogue Act Corpus is adopted and the SWBD-DAMSL tags used for the experiments.Two statistical measures were applied,which include lexical dispersion and lexical similarity using Chi by degrees of freedom(CBDF).We show that the distribution of DAs is uneven,that a majority of the word types occur in one DA and that only a small fraction of word types are commonly used by all the DAs.Our hierarchical clustering of DAs based on CBDF suggests that there is an intrinsic structure of DAs pertaining to fact finding and verification,information provision and inter-speaker agreement and affinity building.The paper concludes with discussions and suggestions for future work.

Differential neuronal reprogramming induced by NeuroD1 from astrocytes in grey matter versus white matter

A new technology called in vivo glia-to-neuron conversion has emerged in recent years as a promising next generation therapy for neural regeneration and repair. This is achieved through reprogramming endogenous glial cells into neurons in the central nervous system through ectopically expressing neural transcriptional factors in glial cells. Previous studies have been focusing on glial cells in the grey matter such as the cortex and striatum, but whether glial cells in the white matter can be reprogrammed or not is unknown. To address this fundamental question, we express NeuroD1 in the astrocytes of both grey matter(cortex and striatum) and white matter(corpus callosum) to investigate the conversion efficiency, neuronal subtypes, and electrophysiological features of the converted neurons. We discover that NeuroD1 can efficiently reprogram the astrocytes in the grey matter into functional neurons, but the astrocytes in the white matter are much resistant to neuronal reprogramming. The converted neurons from cortical and striatal astrocytes are composed of both glutamatergic and GABAergic neurons, capable of firing action potentials and having spontaneous synaptic activities. In contrast, the few astrocyte-converted neurons in the white matter are rather immature with rare synaptic events. These results provide novel insights into the differential reprogramming capability between the astrocytes in the grey matter versus the white matter, and highlight the impact of regional astrocytes as well as microenvironment on the outcome of glia-toneuron conversion. Since human brain has large volume of white matter, this study will provide important guidance for future development of in vivo glia-to-neuron conversion technology into potential clinical therapies. Experimental protocols in this study were approved by the Laboratory Animal Ethics Committee of Jinan University(approval No. IACUC-20180321-03) on March 21, 2018.

An algorithm for voice conversion with limited corpus

Under the condition of limited target speaker＇s corpus, this paper proposed an algorithm for voice conversion using unified tensor dictionary with limited corpus. Firstly, parallel speech of N speakers was selected randomly from the speech corpus to build the base of tensor dictionary. And then, after the operation of multi-series dynamic time warping for those chosen speech, N two-dimension basic dictionaries can be generated which constituted the unified tensor dictionary. During the conversion stage, the two dictionaries of source and target speaker were established by linear combination of the N basic dictionaries using the two speakers＇ speech. The experimental results showed that when the number of the basic speaker was 14, our algorithm can obtain the compared performance of the traditional NMF- based method with few target speaker corpus, which greatly facilitate the application of voice conversion system.

Authenticity and College Oral English Teaching

This paper aims to explore how to bring authenticity into oral English class. By discussing a number of conversational features which are prominent in every day interaction, but are lacking in the standard English material our students are learning every day, we suggest that everyday conversation is different from standard written English, so taking standard written English as a model in our oral English class is not feasible. We believe that applying CL （corpus linguistics） and CA （conversation analysis） into oral English classroom to design the learning material and classroom tasks is a good way to enhance the authenticity of language learning.

The Influence of the Korean Wave on the Language of International Fans： Case Study of Algerian Fans

The linguistic influence of the Korean Wave （Hallyu, which refers to the Korean pop and drama） on the language of International fans is that of a salient but not linguistically examined phenomenon. This study investigates the major aspects of this influence and the linguistic reasons behind its global prevalence. The practical part of this study is conducted on Algerian Hallyu fans from which a sample of 139 participants responded to the questionnaire used as a research instrument for achieving the goal of this study. Findings reveal that Hallyu influence is widely spread in Algeria, where by 98.5% of the participants declared the existence of this influence. This impact on participants＇ language starts from using Korean words in their daily discourse to using English words with an adapted Hallyu meaning and to naming phone contacts with the accurate Korean terms of kinship and endearment. Then, they start using linguistically odd inside jokes taken from Korean idols＇ and K-dramas＇ speech, employing Korean proverbs in their conversations, and gradually adopting a different pronunciation of some English sounds. Moreover, their language stands as a sample of Corpus Planning with two types： Modernization and Graphization. Some words are modernized in order to bridge the gap through Hallyu pals＇ communication with more precise words, while other words are graphitized for the sake of developing new terms or new meanings or to shorten long ones. This thesis contributes to the study of random language, generally, and to Hallyu language, specifically, as an aspect of Conversation Analysis （CA）.