Contemporary media audiences expect to be able to interact with content, but in a minority language context, audience participation presents challenges related to audiences’ linguistic confidence. This thesis focuses on Wales, where media producers have suggested that audiences are often reluctant to interact with broadcast and online content in Welsh. To begin to understand this unwillingness, and how it might be overcome, the concept of willingness to participate (WTP) is coined as an extension of willingness to communicate (McCroskey & Baer 1985). First, interviews with producers are analysed qualitatively to identify potential influences on audiences’ WTP. The analysis aims to assess the relative importance of various factors: audiences’ feelings of apprehension, self‐perceived competence, language background and Welsh language ability, as well as the modality of participation (oral/written) and the level of demand placed on the audience. Second, a questionnaire is designed and administered to 358 Welsh speakers, to examine audiences’ perceptions of different opportunities to participate in media content. A path model of WTP is proposed and tested using quantitative data from the survey. The results support the hypothesis that audiences’ apprehension and self‐perceived competence predict WTP and that audience response varies according to the media context. While audiences’ Welsh language skills are important in explaining their WTP, other aspects of language background, such as Welsh language acquisition context, are found to be less important. Third, the survey sample is grouped according to common patterns of WTP, to test whether the above effects are consistent across the population or whether different ‘types’ of audience exist. Using a combination of cluster analysis and thematic analysis of audience comments, four types of audience are proposed and described in detail. Finally, implications for sociolinguistic theory, language maintenance and media production practice are considered and recommendations made.

This study offers an assessment of the non-native speech intelligibility of a group of English learners of Spanish at word level and in connected speech. Specifically, we aimed at analysing the impact of certain categories of phonemic errors, as well as three temporal variables of L2 speech (speech rate, pause frequency and pause duration) on intelligibility scores. In addition, the possible correlation between degree of intelligibility and certain individual factors (gender, level of proficiency, motivation, aptitude and L1) was also studied. Sixty evaluators, native speakers of Peninsular Spanish, transcribed different speech samples belonging to a group of 20 Key Stage 4 English learners of Spanish. The transcription of the different speech samples served to assess intelligibility at word level and in connected speech (sentence, passage and semi-spontaneous production). Results revealed an intelligibility loss at all levels of analysis, as well as a high correlation between intelligibility scores in the single word test and those obtained in connected speech. At a segmental level, deviations affecting vowels, especially unstressed vowels, seemed to play a more important role than inaccuracies affecting consonants. Moreover, correlation analyses underscored the importance of speech rate, pause frequency and pause duration for intelligibility loss. The predictability of our multiple-regression models was high for speech samples obtained at sentence and passage levels. However, multiple-regression models for speech samples obtained through the semi-spontaneous production task exhibited a more limited capability in predicting variation in students’ intelligibility scores. Results suggest the existence of additional variables affecting intelligibility at this level of analysis. All individual differences under study, with the exception of gender, were highly correlated with speech intelligibility. From a pedagogical perspective, it is argued here that any successful instructional treatment of speech intelligibility will depend on an appropriate integration of temporal aspects of speech within the time devoted to pronunciation instruction in the foreign language classroom.

Unsupervised approaches to learning the morphology of a language play an important role in computer processing of language from a practical and theoretical perspective, due their minimal reliance on manually produced linguistic resources and human annotation. Such approaches have been widely researched for the problem of concatenative affixation, but less attention has been paid to the intercalated (non-concatenative) morphology exhibited by Arabic and other Semitic languages. The aim of this research is to learn the root and pattern morphology of Arabic, with accuracy comparable to manually built morphological analysis systems. The approach is kept free from human supervision or manual parameter settings, assuming only that roots and patterns intertwine to form a word. Promising results were obtained by applying a technique adapted from previous work in concatenative morphology learning, which uses machine learning to determine relatedness between words. The output, with probabilistic relatedness values between words, was then used to rank all possible roots and patterns to form a lexicon. Analysis using trilateral roots resulted in correct root identification accuracy of approximately 86% for inflected words. Although the machine learning-based approach is effective, it is conceptually complex. So an alternative, simpler and computationally efficient approach was then devised to obtain morpheme scores based on comparative counts of roots and patterns. In this approach, root and pattern scores are defined in terms of each other in a mutually recursive relationship, converging to an optimized morpheme ranking. This technique gives slightly better accuracy while being conceptually simpler and more efficient. The approach, after further enhancements, was evaluated on a version of the Quranic Arabic Corpus, attaining a final accuracy of approximately 93%. A comparative evaluation shows this to be superior to two existing, well used manually built Arabic stemmers, thus demonstrating the practical feasibility of unsupervised learning of non-concatenative morphology.

Thesis (M. A.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (Ed.D.)--University of Toronto, 2006. / Includes bibliographical references (leaves 152-162).

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 232-241). Available also in a digital version from Dissertation Abstracts.

Thesis--University of Michigan. / Includes bibliographical references (p. 150-151).

A computer program which can "understand" natural language texts must have both syntactic knowledge about the language concerned and semantic knowledge of how what is written relates to its internal representation of the world. It has been a matter of some controversy how these sources of information can best be integrated to translate from an input text to a formal meaning representation. The controversy has concerned largely the question as to what degree of syntactic analysis must be performed before any semantic analysis can take place. An extreme position in this debate is that a syntactic parse tree for a complete sentence must be produced before any investigation of that sentence's meaning is appropriate. This position has been criticised by those who see understanding as a process that takes place gradually as the text is read, rather than in sudden bursts of activity at the ends of sentences. These people advocate a model where semantic analysis can operate on fragments of text before the global syntactic structure is determined - a strategy which we will call early semantic analysis. In this thesis, we investigate the implications of early semantic analysis in the interpretation of noun phrases. One possible approach is to say that a noun phrase is a self-contained unit and can be fully interpreted by the time it has been read. Thus it can always be determined what objects a noun phrase refers to without consulting much more than the structure of the phrase itself. This approach was taken in part by Winograd [Winograd 72], who saw the constraint that a noun phrase have a referent as a valuable aid in resolving local syntactic ambiguity. Unfortunately, Winograd's work has been criticised by Ritchie, because it is not always possible to determine what a noun phrase refers to purely on the basis of local information. In this thesis, we will go further than this and claim that, because the meaning of a noun phrase can be affected by so many factors outside the phrase itself, it makes no sense to talk about "the referent" as a function of -a noun phrase. Instead, the notion of "referent" is something defined by global issues of structure and consistency. Having rejected one approach to the early semantic analysis of noun phrases, we go on to develop an alternative, which we call incremental evaluation. The basic idea is that a noun phrase does provide some information about what it refers to. It should be possible to represent this partial information and gradually refine it as relevant implications of the context are followed up. Moreover, the partial information should be available to an inference system, which, amongst other things, can detect the absence of a referent and provide the advantages of Winograd's system. In our system, noun phrase interpretation does take place locally, but the point is that it does not finish there. Instead, the determination of the meaning of a noun phrase is spread over the subsequent analysis of how it contributes to the meaning of the text as a whole.

Thesis (Ph.D.)--University of Wollongong, 2006. / Typescript. Includes bibliographical references: leaf 210-218.

Thesis (M.A. (Linguistics))--Mahidol University, 1982.