Automatic Dialect and Accent Recognition and its Application to Speech Recognition

A fundamental challenge for current research on speech science and technology is understanding and modeling individual variation in spoken language. Individuals have their own speaking styles, depending on many factors, such as their dialect and accent as well as their socioeconomic background. These individual differences typically introduce modeling difficulties for large-scale speaker-independent systems designed to process input from any variant of a given language. This dissertation focuses on automatically identifying the dialect or accent of a speaker given a sample of their speech, and demonstrates how such a technology can be employed to improve Automatic Speech Recognition (ASR). In this thesis, we describe a variety of approaches that make use of multiple streams of information in the acoustic signal to build a system that recognizes the regional dialect and accent of a speaker. In particular, we examine frame-based acoustic, phonetic, and phonotactic features, as well as high-level prosodic features, comparing generative and discriminative modeling techniques. We first analyze the effectiveness of approaches to language identification that have been successfully employed by that community, applying them here to dialect identification. We next show how we can improve upon these techniques. Finally, we introduce several novel modeling approaches -- Discriminative Phonotactics and kernel-based methods. We test our best performing approach on four broad Arabic dialects, ten Arabic sub-dialects, American English vs. Indian English accents, American English Southern vs. Non-Southern, American dialects at the state level plus Canada, and three Portuguese dialects. Our experiments demonstrate that our novel approach, which relies on the hypothesis that certain phones are realized differently across dialects, achieves new state-of-the-art performance on most dialect recognition tasks. This approach achieves an Equal Error Rate (EER) of 4% for four broad Arabic dialects, an EER of 6.3% for American vs. Indian English accents, 14.6% for American English Southern vs. Non-Southern dialects, and 7.9% for three Portuguese dialects. Our framework can also be used to automatically extract linguistic knowledge, specifically the context-dependent phonetic cues that may distinguish one dialect form another. We illustrate the efficacy of our approach by demonstrating the correlation of our results with geographical proximity of the various dialects. As a final measure of the utility of our studies, we also show that, it is possible to improve ASR. Employing our dialect identification system prior to ASR to identify the Levantine Arabic dialect in mixed speech of a variety of dialects allows us to optimize the engine's language model and use Levantine-specific acoustic models where appropriate. This procedure improves the Word Error Rate (WER) for Levantine by 4.6% absolute; 9.3% relative. In addition, we demonstrate in this thesis that, using a linguistically-motivated pronunciation modeling approach, we can improve the WER of a state-of-the art ASR system by 2.2% absolute and 11.5% relative WER on Modern Standard Arabic

A Corpus-based Study of the English Translation of Chinese Empty Words

This study aims to investigate the translation procedures adopted for the English translation of Chinese empty words. To begin with, the methods which translators adopt to tackle empty words are identified by examining examples in a specially-constructed parallel corpus, which includes Chinese literary texts and their English translations. Eventually, eight translation procedures (1) Match; 2) Paraphrase; 3) Shared Match; 4) Implicitation; 5) Amplification; 6) Grammatical Conveyance; 7) Borrowing; 8) Omission) and one non-procedure (Mismatch) are identified. It is noted that Grammatical Conveyance is a procedure which could be deemed as a newly-identified method. As a further step, the proportion of these procedures/non-procedure is investigated to identify the most-/least-adopted ones (Match and Amplification respectively) and to discuss category-specific ones (Shared Match and Borrowing). In addition to identifying the procedures for translating Chinese empty words into English, this research also makes contributions in the following two aspects. Firstly, this study, to my knowledge, is the first research which examines all Chinese empty words at a time to identify the ways translators tackle them. Secondly, it is known from the results that difficult-to-tackle empty words are found in the categories of Adverb and Particle. In other words, not all empty words are difficult to translate as former scholars have described

Language maintenance through primary school education: the case of Daighi

Ongoing language shift to Taiwanese Mandarin is a pressing concern in Taiwan. With the concerns of losing the rich linguistic and cultural assets of Taiwan’s multilingual society, this study sets out to explore the language maintenance endeavours in primary schools, focusing on Daighi. Exploration of language attitudes is the angle this study adopts to approach language shift, looking specifically at whether language attitudes are promoted through the mandatory local languages class at primary school level. However, a large piece of the picture would be missed without the evaluation of the context, which is crucial to understand Daighi’s position. Sociocultural theory is then adopted as an analytical lens to view teachers’ practices as mediated actions, and to make visible the impact of context in Daighi maintenance. Interviews are used to explore the insights of the frontline Daighi teachers, and Daighi classes of these teachers are observed to investigate their practices, and to match these with their perceptions. In spite of the good teaching practices found at schools and attitudes to support language maintenance, there is still a gap in terms of actual language maintenance, which is defined as developing students to become functional bilinguals (Li Wei, 2006). It is possible that language maintenance is not best achieved by focusing on classroom practice alone. The Discussion Chapter then presents the mediators from global level, national level to classroom, students and teacher agency. Language policy, educational system, and perceived language attitudes of the government, local authority, school, colleagues, family and students emerge as influential mediators that contribute to the ongoing language shift to Taiwanese Mandarin. This study provides an analytical insight into Taiwanese local language education and language attitudes. Through engaging with the teachers, it also inspired critical reflections of their own practices. The findings of this study demonstrate an in-depth understanding of Daighi maintenance and shift, and provide a starting point for further research in Daighi, and in the area of language maintenance in multilingual settings