Why Don't Students Talk? Causes of Foreign Language Communication Apprehension in English Classes: A Comparison of High Apprehensive and Low Apprehensive Upper Secondary Students.

OBJECTIVES. Oral foreign language skills are an integral part of one's social, academic and professional competence. This can be problematic for those suffering from foreign language communication apprehension (CA), or a fear of speaking a foreign language. CA manifests itself, for example, through feelings of anxiety and tension, physical arousal and avoidance of foreign language communication situations. According to scholars, foreign language CA may impede the language learning process significantly and have detrimental effects on one's language learning, academic achievement and career prospects. Drawing on upper secondary students' subjective experiences of communication situations in English as a foreign language, this study seeks, first, to describe, analyze and interpret why upper secondary students experience English language communication apprehension in English as a foreign language (EFL) classes. Second, this study seeks to analyse what the most anxiety-arousing oral production tasks in EFL classes are, and which features of different oral production tasks arouse English language communication apprehension and why. The ultimate objectives of the present study are to raise teachers' awareness of foreign language CA and its features, manifestations and impacts in foreign language classes as well as to suggest possible ways to minimize the anxiety-arousing features in foreign language classes. METHODS. The data was collected in two phases by means of six-part Likert-type questionnaires and theme interviews, and analysed using both quantitative and qualitative methods. The questionnaire data was collected in spring 2008. The respondents were 122 first-year upper secondary students, 68 % of whom were girls and 31 % of whom were boys. The data was analysed by statistical methods using SPSS software. The theme interviews were conducted in spring 2009. The interviewees were 11 second-year upper secondary students aged 17 to 19, who were chosen by purposeful selection on the basis of their English language CA level measured in the questionnaires. Six interviewees were classified as high apprehensives and five as low apprehensives according to their score in the foreign language CA scale in the questionnaires. The interview data was coded and thematized using the technique of content analysis. The analysis and interpretation of the data drew on a comparison of the self-reports of the highly apprehensive and low apprehensive upper secondary students. RESULTS. The causes of English language CA in EFL classes as reported by the students were both internal and external in nature. The most notable causes were a low self-assessed English proficiency, a concern over errors, a concern over evaluation, and a concern over the impression made on others. Other causes related to a high English language CA were a lack of authentic oral practise in EFL classes, discouraging teachers and negative experiences of learning English, unrealistic internal demands for oral English performance, high external demands and expectations for oral English performance, the conversation partner's higher English proficiency, and the audience's large size and unfamiliarity. The most anxiety-arousing oral production tasks in EFL classes were presentations or speeches with or without notes in front of the class, acting in front of the class, pair debates with the class as audience, expressing thoughts and ideas to the class, presentations or speeches without notes while seated, group debates with the class as audience, and answering to the teacher's questions involuntarily. The main features affecting the anxiety-arousing potential of an oral production task were a high degree of attention, a large audience, a high degree of evaluation, little time for preparation, little linguistic support, and a long duration.

Ordered Ports – a Language Concept for High-level Distributed Programming

A new language concept for high-level distributed programming is proposed. Programs are organised as a collection of concurrently executing processes. Some of these processes, referred to as liaison processes, have a monitor-like structure and contain ports which may be invoked by other processes for the purposes of synchronisation and communication. Synchronisation is achieved by conditional activation of ports and also through port control constructs which may directly specify the execution ordering of ports. These constructs implement a path-expression-like mechanism for synchronisation and are also equipped with options to provide conditional, non-deterministic and priority ordering of ports. The usefulness and expressive power of the proposed concepts are illustrated through solutions of several representative programming problems. Some implementation issues are also considered.

Language universals and linguistic complexity : Three case studies in core argument marking

In this dissertation I study language complexity from a typological perspective. Since the structuralist era, it has been assumed that local complexity differences in languages are balanced out in cross-linguistic comparisons and that complexity is not affected by the geopolitical or sociocultural aspects of the speech community. However, these assumptions have seldom been studied systematically from a typological point of view. My objective is to define complexity so that it is possible to compare it across languages and to approach its variation with the methods of quantitative typology. My main empirical research questions are: i) does language complexity vary in any systematic way in local domains, and ii) can language complexity be affected by the geographical or social environment? These questions are studied in three articles, whose findings are summarized in the introduction to the dissertation. In order to enable cross-language comparison, I measure complexity as the description length of the regularities in an entity; I separate it from difficulty, focus on local instead of global complexity, and break it up into different types. This approach helps avoid the problems that plagued earlier metrics of language complexity. My approach to grammar is functional-typological in nature, and the theoretical framework is basic linguistic theory. I delimit the empirical research functionally to the marking of core arguments (the basic participants in the sentence). I assess the distributions of complexity in this domain with multifactorial statistical methods and use different sampling strategies, implementing, for instance, the Greenbergian view of universals as diachronic laws of type preference. My data come from large and balanced samples (up to approximately 850 languages), drawn mainly from reference grammars. The results suggest that various significant trends occur in the marking of core arguments in regard to complexity and that complexity in this domain correlates with population size. These results provide evidence that linguistic patterns interact among themselves in terms of complexity, that language structure adapts to the social environment, and that there may be cognitive mechanisms that limit complexity locally. My approach to complexity and language universals can therefore be successfully applied to empirical data and may serve as a model for further research in these areas.

FIN-CLARIN: A Framework for Depositing and Disseminating Language Resources for R&D

Researchers and developers in academia and industry would benefit from a facility that enables them to easily locate, licence and use the kind of empirical data they need for testing and refining their hypotheses and to deposit and disseminate their data e.g. to support replication and validation of reported scientific experiments. To answer these needs initially in Finland, there is an ongoing project at University of Helsinki and its collaborators to create a user-friendly web service for researchers and developers in Finland and other countries. In our talk, we describe ongoing work to create a palette of extensive but easily available Finnish language resources and technologies for the research community, including lexical resources, wordnets, morphologically tagged corpora, dependency syntactic treebanks and parsebanks, open-source finite state toolkits and libraries and language models to support text analysis and processing at customer site. Also first publicly available results are presented.

META-NORD: Towards Sharing of Language Resources in Nordic and Baltic Countries

This paper introduces the META-NORD project which develops Nordic and Baltic part of the European open language resource infrastructure. META-NORD works on assembling, linking across languages, and making widely available the basic language resources used by developers, professionals and researchers to build specific products and applications. The goals of the project, overall approach and specific focus lines on wordnets, terminology resources and treebanks are described. Moreover, results achieved in first five months of the project, i.e. language whitepapers, metadata specification and IPR, are presented.

Finite-State Spell-Checking with Weighted Language and Error Models

In this paper we present simple methods for construction and evaluation of finite-state spell-checking tools using an existing finite-state lexical automaton, freely available finite-state tools and Internet corpora acquired from projects such as Wikipedia. As an example, we use a freely available open-source implementation of Finnish morphology, made with traditional finite-state morphology tools, and demonstrate rapid building of Northern Sámi and English spell checkers from tools and resources available from the Internet.

Pruned Universal Symbol Sequences for LZW based Language identification

We present a improved language modeling technique for Lempel-Ziv-Welch (LZW) based LID scheme. The previous approach to LID using LZW algorithm prepares the language pattern table using LZW algorithm. Because of the sequential nature of the LZW algorithm, several language specific patterns of the language were missing in the pattern table. To overcome this, we build a universal pattern table, which contains all patterns of different length. For each language it's corresponding language specific pattern table is constructed by retaining the patterns of the universal table whose frequency of appearance in the training data is above the threshold.This approach reduces the classification score (Compression Ratio [LZW-CR] or the weighted discriminant score[LZW-WDS]) for non native languages and increases the LID performance considerably.

LZW Based Distance Measures for Spoken Language Identification

We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.