Good English Pronunciation Users and their Pronunciation Learning Strategies

The study investigates pronunciation learning strategies (PLS) deployed by those with good English pronunciation, as well as their beliefs concerning the variables that affect pronunciation competence. In order to collect data for analysis this study surveyed 61 participants who had learned English as a foreign language. They comprised 28 higher education teachers and scholars specialising in English phonetics and phonology, who were defined as good pronunciation users (GPU), and 33 EFL teacher training students, viewed as average pronunciation learners (APL). This cohort responded to a survey on pronunciation learning strategies and expressed their views on several aspects affecting the L2 pronunciation learning process. These aspects were: age of the first contact with L2 (age of onset), motivation, exposure to the target language, the teacher’s pronunciation model, and learning strategies. The study used both open- and close-ended question formats to collect data from both GPU and APL. The analyses of the data helped to create a tentative profile of a successful L2 pronunciation learner

Effects of corrective feedback on EFL speaking task complexity in China’s university classroom

Corrective feedback (CF) and task complexity are two important pedagogical topics in second language acquisition research in recent years, but there is few research investigating effects of CF on speaking task complexity in China’s university classroom settings. This research, through conducting different versions of speaking task experiments among 24 university students in China, explores the effect of teachers’ CF on English as a Foreign Language (EFL) speaking task complexity. According to the analysis of first-hand data, this research finds CF has different effects on EFL oral production with different task complexity. In simple speaking task, the effects of five kinds of CF (from largest to smallest) are listed as follows: clarification quest, metalinguistic feedback, recast, repetition and confirmation check. Regarding complex speaking task, the effects of five categorized CF are ranked from largest to smallest as follows: metalinguistic feedback, confirmation check, recast, clarification request and repetition. Improving to provide CF in pedagogical practice is an important contribution to promote EFL speaking task, so, on the basis of above research results, appropriate ways and forms of providing CF are expected to promote efficiency of CF in EFL classroom under the context of Chinese university classroom

Meta-Learning for Phonemic Annotation of Corpora

We apply rule induction, classifier combination and meta-learning (stacked classifiers) to the problem of bootstrapping high accuracy automatic annotation of corpora with pronunciation information. The task we address in this paper consists of generating phonemic representations reflecting the Flemish and Dutch pronunciations of a word on the basis of its orthographic representation (which in turn is based on the actual speech recordings). We compare several possible approaches to achieve the text-to-pronunciation mapping task: memory-based learning, transformation-based learning, rule induction, maximum entropy modeling, combination of classifiers in stacked learning, and stacking of meta-learners. We are interested both in optimal accuracy and in obtaining insight into the linguistic regularities involved. As far as accuracy is concerned, an already high accuracy level (93% for Celex and 86% for Fonilex at word level) for single classifiers is boosted significantly with additional error reductions of 31% and 38% respectively using combination of classifiers, and a further 5% using combination of meta-learners, bringing overall word level accuracy to 96% for the Dutch variant and 92% for the Flemish variant. We also show that the application of machine learning methods indeed leads to increased insight into the linguistic regularities determining the variation between the two pronunciation variants studied.Comment: 8 page

Do not forget: Full memory in memory-based learning of word pronunciation

Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior in generalisation accuracy to eager learning approaches that abstract from learning material. Here we investigate three partial memory-based learning approaches which remove from memory specific task instance types estimated to be exceptional. The three approaches each implement one heuristic function for estimating exceptionality of instance types: (i) typicality, (ii) class prediction strength, and (iii) friendly-neighbourhood size. Experiments are performed with the memory-based learning algorithm IB1-IG trained on English word pronunciation. We find that removing instance types with low prediction strength (ii) is the only tested method which does not seriously harm generalisation accuracy. We conclude that keeping full memory of types rather than tokens, and excluding minority ambiguities appear to be the only performance-preserving optimisations of memory-based learning.Comment: uses conll98, epsf, and ipamacs (WSU IPA

English for Young Learners Teachers Strategy in Teaching Reading

Penelitian ini bertujuan untuk 1) mengetahui strategi -strategi yang digunakan oleh para pengajar bahasa Inggris di dalam pengajaran Reading for Young Learners, 2)mengetahui hambatan-hambatan yang dihadapi oleh para pengajar bahasa Inggris di dalam mengajar Reading for Young Learners, dan 3) mendeskripsikan cara para pengajar mengatasi hambatan-hambatan di dalam mengajar Reading for Young Learners.Penelitian ini dilakukan di lima sekolah yang berbeda di Jepara, Jawa Tengah.Penelitian ini dapat menjadi deskripsi mengenai strategi -strategi pembelajaran bahasa yang sangat penting di dalam proses pengajaran dan pembelajaran English for YoungLearners (EYL). Penelitian ini menggunakan penelitian kualitatif dalam bentuk studi kasus. Data diperoleh melalui observasi, wawancara, dokumentasi, dan kuesioner.Berdasarkan pada data yang ditemukan, dapat disimpulkan bahwa para pengajar Bahasa Inggris di dalam mengajar Reading menggunakan strategi-strategi yang berbeda, yang didasarkan pada kebutuhan siswa dan kondisi sekolah. Strategi strategi tersebut digunakan untuk mengatasi permasalahan yang dihadapi di selama proses pengajaran dan pembelajaran. Hasil dari kuesioner menunjukkan bahwa para siswa menyukai bahasa Inggris, bukan para pengajarnya. Sehingga para pengajar perlumengimplementasikan strategi-strategi yang baik dan tepat dalam memenuhi kebutuhan para siswa

A Comparison of Different Machine Transliteration Models

Machine transliteration is a method for automatically converting words in one language into phonetically equivalent ones in another language. Machine transliteration plays an important role in natural language applications such as information retrieval and machine translation, especially for handling proper nouns and technical terms. Four machine transliteration models -- grapheme-based transliteration model, phoneme-based transliteration model, hybrid transliteration model, and correspondence-based transliteration model -- have been proposed by several researchers. To date, however, there has been little research on a framework in which multiple transliteration models can operate simultaneously. Furthermore, there has been no comparison of the four models within the same framework and using the same data. We addressed these problems by 1) modeling the four models within the same framework, 2) comparing them under the same conditions, and 3) developing a way to improve machine transliteration through this comparison. Our comparison showed that the hybrid and correspondence-based models were the most effective and that the four models can be used in a complementary manner to improve machine transliteration performance

The Teaching of English Vocabulary through the Multisensory Approach to Older Adults in a Private Nursing Home in Pereira, Colombia

El siguiente documento es un proyecto de investigación cualitativo cuyo objetivo es integrar la teoría andragógica y el enfoque multisensorial para facilitar el aprendizaje de vocabulario en inglés a adultos mayores. Adicionalmente, este estudio es una iniciativa para incluir a los adultos mayores en un proceso de educación bilingüe ya que esta población casi no ha sido tomada en cuenta para la realización de proyectos bilingües. Por esta razón, este proyecto propone nuevas oportunidades para futuras investigaciones El presente estudio fue implementado en el hogar del anciano Casa Santa María en Pereira, Colombia. Este proyecto fue llevado a cabo en 10 clases en las cuales las participantes aprendieron 47 palabras relacionadas con su contexto inmediato. Las participantes del proyecto fueron cuatro mujeres, quienes tenían más de 60 años de edad. Las cuatro fueron consideradas como un proceso de muestreo típico intencional para recopilar los datos, los cuales fueron interpretados por los investigadores. Además, durante la implementación del estudio, tres métodos de recolección de datos fueron empleados: observaciones, diarios de campo, y entrevistas. Los datos recogidos fueron analizados aplicando la teoría fundada, y después de este análisis los datos sugirieron que a) las estrategias de aprendizaje autodirigido pueden facilitar el éxito del aprendizaje de vocabulario y b) los sentidos de los adultos mayores tienen diferentes usos dependiendo de la etapa de la clase. Para concluir, el enfoque multisensorial es efectivo para enseñar vocabulario en inglés a adultos mayores junto con los principios andragógicos

Forgetting Exceptions is Harmful in Language Learning

We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for generalization accuracy. We investigate this phenomenon empirically on a selection of benchmark natural language processing tasks: grapheme-to-phoneme conversion, part-of-speech tagging, prepositional-phrase attachment, and base noun phrase chunking. In a first series of experiments we combine memory-based learning with training set editing techniques, in which instances are edited based on their typicality and class prediction strength. Results show that editing exceptional instances (with low typicality or low class prediction strength) tends to harm generalization accuracy. In a second series of experiments we compare memory-based learning and decision-tree learning methods on the same selection of tasks, and find that decision-tree learning often performs worse than memory-based learning. Moreover, the decrease in performance can be linked to the degree of abstraction from exceptions (i.e., pruning or eagerness). We provide explanations for both results in terms of the properties of the natural language processing tasks and the learning algorithms.Comment: 31 pages, 7 figures, 10 tables. uses 11pt, fullname, a4wide tex styles. Pre-print version of article to appear in Machine Learning 11:1-3, Special Issue on Natural Language Learning. Figures on page 22 slightly compressed to avoid page overloa

Immediate and Distracted Imitation in Second-Language Speech: Unreleased Plosives in English

The paper investigates immediate and distracted imitation in second-language speech using unreleased plosives. Unreleased plosives are fairly frequently found in English sequences of two stops. Polish, on the other hand, is characterised by a significant rate of releases in such sequences. This cross-linguistic difference served as material to look into how and to what extent non-native properties of sounds can be produced in immediate and distracted imitation. Thirteen native speakers of Polish first read and then imitated sequences of words with two stops straddling the word boundary. Stimuli for imitation had no release of the first stop. The results revealed that (1) a non-native feature such as the lack of the release burst can be imitated; (2) distracting imitation impedes imitative performance; (3) the type of a sequence interacts with the magnitude of an imitative effec