129 research outputs found

    INSTRUCTIONAL METHODS FOR PROMOTING THE DEVELOPMENT OF ORTHOGRAPHIC AND PHONOLOGICAL KNOWLEDGE IN SECOND LANGUAGE LEARNERS OF INDIC LANGUAGES

    Get PDF
    In three experiments, I test whether the application of particular instructional principles improves the teaching of the orthographic and phonological systems of Indic languages to second language learners. In Experiment 1, I developed a mobile game that teaches 4th grade children Hindi decoding skills, with an emphasis on complex akshara. There were two versions of the game that varied in terms of stimuli spacing (narrow and wide). I found that the game improved participantsโ€™ akshara recognition and their ability to read and spell words that contain complex akshara. Both versions of the game yielded equivalent levels of improvement, but participants played the narrow spacing version faster. Analysis of the game data revealed interesting patterns of common mistakes. Children struggled with akshara that were non-linear and opaque. When spelling words, children struggled when the complex akshara crossed a syllabic boundary and they often made phonological errors. In Experiment 2, I examined whether motor encoding and testing benefit orthographic learning. I found that motor encoding benefits orthographic learning when tasks require pure orthographic knowledge or the production of an orthographic form when given a phonological form. Testing does not benefit beginning learners. In Experiment 3, I tested whether pedagogical differences or individual differences affect the learning of non-native phonemic contrasts. I found that learning of the difficult dental/retroflex contrast can be improved by increasing the voice onset times of the dental sounds. Both English phonological skills and rise time discrimination positively predict learning the non-native contrasts. Furthermore, pairing phonemes with English transliterations impairs discrimination learning, likely because of interference from the English pronunciation. Orthographic support helps people remember which phonemes are in words. Therefore, the use of akshara can benefit second language learners because the graphs are not already associated with phonological referents and the graphs help people remember which phonemes are in vocabulary words. When considered together, these three experiments suggest that multisensory encoding and reducing interference benefit second language learners

    L2 Korean Phonology: the acquisition of stops by English-and Finnish-speaking adults

    Get PDF
    The purpose of this thesis is to find the reason why attaining nativelike pronunciation is difficult in adult L2A. This thesis attempts to take a purely linguistic approach to find it by hypothising that the acquisition of segmental phonology is more than the physical matter of getting the articulators to move correctly and involves phonological rules and principles. The hypothesis was tested through the L2A of Korean stops, which was investigated in three parts; perception of stop segments in word-initial position, production of stop segments in word-initial position and production of stops involving phonological rules constrained by syntax (i.e. the tensification rule vs. the intervocalic voicing rule).Thirteen British English-speaking adults and fifteen Finnish-speaking adults participated in the experiment. The research subjects were divided into three different groups ('Inexperienced I'๏ผŒ 'Inexperienced n' and 'Experienced') according to the length of exposure to Korean. The subjects in the group of 'Inexperienced ฤพ were exposed to Korean for one year in their native countries, and the subjects in the group of 'Inexperienced 11' for two years in their native countries. The subjects in the group of 'Experienced' attended a Korean language course for one academic year at least in Korea. Firstly, as for perception of stop segments in word-initial position, both English- and Finnish-speaking learners performed better in discerning geminates from non- geminate segment in general. Especially, the two language groups of learners were native-like in discerning a geminate (AA) from a non-geminate of which the segment is different from the ones in the geminate (B). On the contrary, the Korean stops distinguished by the feature [sg] alone have appeared the most difficult for the L2 learners of Korean to acquire. The English- and Finnish-Speaking learners showed a similar pattern of difficulties in discerning Korean stops regarding the feature [sg]; however, differences between the two language groups were also found in the perception of word-initial Korean stops, which were caused by the absence or presence of geminate in the learners' L1. On the other hand, no progress was made by English- and Finnish-speaking learners in the acquisition of Korean stops in accordance with the length of exposure to Korean. Secondly, the production of word-initial stop segments appeared more successful than the perception of them. The difficulty in producing word-initial stops seemed to be caused by Korean-particular phonological representations rather than controlling the degree of VOT values. As for the developmental aspect, English- and Finnish-speaking learners showed the improvement in the segmental production task according to the length of exposure to Korean unlike in the segmental perception task. Thirdly, the English- and Finnish-speaking I earners performed equally poorly on the tensification rule despite the differences in their L1โ€™s. One reason was that the learners in both language groups were not advanced enough to sense the interaction between the phonological rule and syntactic condition in the Korean grammar. Another reason was orthographic influence. Regardless of the two language groups' similarly poor results in performance on the tensification rule, it was presumed that only Finnish speakers would be able to acquire the Korean-specific rule with the supposition that positive L1 transfer might occur at the even advanced stages of learning. In the light of the findings, it was concluded that the hypothesis of this thesis was supported by results from the experiment. Observing that the L2 learners had far greater difficulty in their production of stops involved in the tensification rule constrained by syntax than in their production of word-initial stops, it is concluded that the difficulty of mastering L2 phonology is due to the complexity of phonological rules applying beyond the component of phonology or across phonological domains in the prosodie hierarchy, some of which provide a means for mapping the syntax to the phonology. Therefore, all the complex phonological rules and principles of a segment must be acquired for the target pronunciation

    CAPT๋ฅผ ์œ„ํ•œ ๋ฐœ์Œ ๋ณ€์ด ๋ถ„์„ ๋ฐ CycleGAN ๊ธฐ๋ฐ˜ ํ”ผ๋“œ๋ฐฑ ์ƒ์„ฑ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ธ๋ฌธ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ธ์ง€๊ณผํ•™์ „๊ณต,2020. 2. ์ •๋ฏผํ™”.Despite the growing popularity in learning Korean as a foreign language and the rapid development in language learning applications, the existing computer-assisted pronunciation training (CAPT) systems in Korean do not utilize linguistic characteristics of non-native Korean speech. Pronunciation variations in non-native speech are far more diverse than those observed in native speech, which may pose a difficulty in combining such knowledge in an automatic system. Moreover, most of the existing methods rely on feature extraction results from signal processing, prosodic analysis, and natural language processing techniques. Such methods entail limitations since they necessarily depend on finding the right features for the task and the extraction accuracies. This thesis presents a new approach for corrective feedback generation in a CAPT system, in which pronunciation variation patterns and linguistic correlates with accentedness are analyzed and combined with a deep neural network approach, so that feature engineering efforts are minimized while maintaining the linguistically important factors for the corrective feedback generation task. Investigations on non-native Korean speech characteristics in contrast with those of native speakers, and their correlation with accentedness judgement show that both segmental and prosodic variations are important factors in a Korean CAPT system. The present thesis argues that the feedback generation task can be interpreted as a style transfer problem, and proposes to evaluate the idea using generative adversarial network. A corrective feedback generation model is trained on 65,100 read utterances by 217 non-native speakers of 27 mother tongue backgrounds. The features are automatically learnt in an unsupervised way in an auxiliary classifier CycleGAN setting, in which the generator learns to map a foreign accented speech to native speech distributions. In order to inject linguistic knowledge into the network, an auxiliary classifier is trained so that the feedback also identifies the linguistic error types that were defined in the first half of the thesis. The proposed approach generates a corrected version the speech using the learners own voice, outperforming the conventional Pitch-Synchronous Overlap-and-Add method.์™ธ๊ตญ์–ด๋กœ์„œ์˜ ํ•œ๊ตญ์–ด ๊ต์œก์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ๊ณ ์กฐ๋˜์–ด ํ•œ๊ตญ์–ด ํ•™์Šต์ž์˜ ์ˆ˜๊ฐ€ ํฌ๊ฒŒ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์Œ์„ฑ์–ธ์–ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์„ ์ ์šฉํ•œ ์ปดํ“จํ„ฐ ๊ธฐ๋ฐ˜ ๋ฐœ์Œ ๊ต์œก(Computer-Assisted Pronunciation Training; CAPT) ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๋˜ํ•œ ์ ๊ทน์ ์œผ๋กœ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ˜„์กดํ•˜๋Š” ํ•œ๊ตญ์–ด ๋งํ•˜๊ธฐ ๊ต์œก ์‹œ์Šคํ…œ์€ ์™ธ๊ตญ์ธ์˜ ํ•œ๊ตญ์–ด์— ๋Œ€ํ•œ ์–ธ์–ดํ•™์  ํŠน์ง•์„ ์ถฉ๋ถ„ํžˆ ํ™œ์šฉํ•˜์ง€ ์•Š๊ณ  ์žˆ์œผ๋ฉฐ, ์ตœ์‹  ์–ธ์–ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ  ๋˜ํ•œ ์ ์šฉ๋˜์ง€ ์•Š๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ๊ฐ€๋Šฅํ•œ ์›์ธ์œผ๋กœ์จ๋Š” ์™ธ๊ตญ์ธ ๋ฐœํ™” ํ•œ๊ตญ์–ด ํ˜„์ƒ์— ๋Œ€ํ•œ ๋ถ„์„์ด ์ถฉ๋ถ„ํ•˜๊ฒŒ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜๋‹ค๋Š” ์ , ๊ทธ๋ฆฌ๊ณ  ๊ด€๋ จ ์—ฐ๊ตฌ๊ฐ€ ์žˆ์–ด๋„ ์ด๋ฅผ ์ž๋™ํ™”๋œ ์‹œ์Šคํ…œ์— ๋ฐ˜์˜ํ•˜๊ธฐ์—๋Š” ๊ณ ๋„ํ™”๋œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๋Š” ์ ์ด ์žˆ๋‹ค. ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ CAPT ๊ธฐ์ˆ  ์ „๋ฐ˜์ ์œผ๋กœ๋Š” ์‹ ํ˜ธ์ฒ˜๋ฆฌ, ์šด์œจ ๋ถ„์„, ์ž์—ฐ์–ด์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•๊ณผ ๊ฐ™์€ ํŠน์ง• ์ถ”์ถœ์— ์˜์กดํ•˜๊ณ  ์žˆ์–ด์„œ ์ ํ•ฉํ•œ ํŠน์ง•์„ ์ฐพ๊ณ  ์ด๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ์ถ”์ถœํ•˜๋Š” ๋ฐ์— ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•œ ์‹ค์ •์ด๋‹ค. ์ด๋Š” ์ตœ์‹  ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜ ์–ธ์–ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•จ์œผ๋กœ์จ ์ด ๊ณผ์ • ๋˜ํ•œ ๋ฐœ์ „์˜ ์—ฌ์ง€๊ฐ€ ๋งŽ๋‹ค๋Š” ๋ฐ”๋ฅผ ์‹œ์‚ฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋จผ์ € CAPT ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ์— ์žˆ์–ด ๋ฐœ์Œ ๋ณ€์ด ์–‘์ƒ๊ณผ ์–ธ์–ดํ•™์  ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์™ธ๊ตญ์ธ ํ™”์ž๋“ค์˜ ๋‚ญ๋…์ฒด ๋ณ€์ด ์–‘์ƒ๊ณผ ํ•œ๊ตญ์–ด ์›์–ด๋ฏผ ํ™”์ž๋“ค์˜ ๋‚ญ๋…์ฒด ๋ณ€์ด ์–‘์ƒ์„ ๋Œ€์กฐํ•˜๊ณ  ์ฃผ์š”ํ•œ ๋ณ€์ด๋ฅผ ํ™•์ธํ•œ ํ›„, ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„์„ ํ†ตํ•˜์—ฌ ์˜์‚ฌ์†Œํ†ต์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ค‘์š”๋„๋ฅผ ํŒŒ์•…ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์ข…์„ฑ ์‚ญ์ œ์™€ 3์ค‘ ๋Œ€๋ฆฝ์˜ ํ˜ผ๋™, ์ดˆ๋ถ„์ ˆ ๊ด€๋ จ ์˜ค๋ฅ˜๊ฐ€ ๋ฐœ์ƒํ•  ๊ฒฝ์šฐ ํ”ผ๋“œ๋ฐฑ ์ƒ์„ฑ์— ์šฐ์„ ์ ์œผ๋กœ ๋ฐ˜์˜ํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๊ต์ •๋œ ํ”ผ๋“œ๋ฐฑ์„ ์ž๋™์œผ๋กœ ์ƒ์„ฑํ•˜๋Š” ๊ฒƒ์€ CAPT ์‹œ์Šคํ…œ์˜ ์ค‘์š”ํ•œ ๊ณผ์ œ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด ๊ณผ์ œ๊ฐ€ ๋ฐœํ™”์˜ ์Šคํƒ€์ผ ๋ณ€ํ™”์˜ ๋ฌธ์ œ๋กœ ํ•ด์„์ด ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ๋ณด์•˜์œผ๋ฉฐ, ์ƒ์„ฑ์  ์ ๋Œ€ ์‹ ๊ฒฝ๋ง (Cycle-consistent Generative Adversarial Network; CycleGAN) ๊ตฌ์กฐ์—์„œ ๋ชจ๋ธ๋งํ•˜๋Š” ๊ฒƒ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. GAN ๋„คํŠธ์›Œํฌ์˜ ์ƒ์„ฑ๋ชจ๋ธ์€ ๋น„์›์–ด๋ฏผ ๋ฐœํ™”์˜ ๋ถ„ํฌ์™€ ์›์–ด๋ฏผ ๋ฐœํ™” ๋ถ„ํฌ์˜ ๋งคํ•‘์„ ํ•™์Šตํ•˜๋ฉฐ, Cycle consistency ์†์‹คํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๋ฐœํ™”๊ฐ„ ์ „๋ฐ˜์ ์ธ ๊ตฌ์กฐ๋ฅผ ์œ ์ง€ํ•จ๊ณผ ๋™์‹œ์— ๊ณผ๋„ํ•œ ๊ต์ •์„ ๋ฐฉ์ง€ํ•˜์˜€๋‹ค. ๋ณ„๋„์˜ ํŠน์ง• ์ถ”์ถœ ๊ณผ์ •์ด ์—†์ด ํ•„์š”ํ•œ ํŠน์ง•๋“ค์ด CycleGAN ํ”„๋ ˆ์ž„์›Œํฌ์—์„œ ๋ฌด๊ฐ๋… ๋ฐฉ๋ฒ•์œผ๋กœ ์Šค์Šค๋กœ ํ•™์Šต๋˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ์–ธ์–ด ํ™•์žฅ์ด ์šฉ์ดํ•œ ๋ฐฉ๋ฒ•์ด๋‹ค. ์–ธ์–ดํ•™์  ๋ถ„์„์—์„œ ๋“œ๋Ÿฌ๋‚œ ์ฃผ์š”ํ•œ ๋ณ€์ด๋“ค ๊ฐ„์˜ ์šฐ์„ ์ˆœ์œ„๋Š” Auxiliary Classifier CycleGAN ๊ตฌ์กฐ์—์„œ ๋ชจ๋ธ๋งํ•˜๋Š” ๊ฒƒ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์˜ CycleGAN์— ์ง€์‹์„ ์ ‘๋ชฉ์‹œ์ผœ ํ”ผ๋“œ๋ฐฑ ์Œ์„ฑ์„ ์ƒ์„ฑํ•จ๊ณผ ๋™์‹œ์— ํ•ด๋‹น ํ”ผ๋“œ๋ฐฑ์ด ์–ด๋–ค ์œ ํ˜•์˜ ์˜ค๋ฅ˜์ธ์ง€ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ด๋Š” ๋„๋ฉ”์ธ ์ง€์‹์ด ๊ต์ • ํ”ผ๋“œ๋ฐฑ ์ƒ์„ฑ ๋‹จ๊ณ„๊นŒ์ง€ ์œ ์ง€๋˜๊ณ  ํ†ต์ œ๊ฐ€ ๊ฐ€๋Šฅํ•˜๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค๋Š” ๋ฐ์— ๊ทธ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด์„œ 27๊ฐœ์˜ ๋ชจ๊ตญ์–ด๋ฅผ ๊ฐ–๋Š” 217๋ช…์˜ ์œ ์˜๋ฏธ ์–ดํœ˜ ๋ฐœํ™” 65,100๊ฐœ๋กœ ํ”ผ๋“œ๋ฐฑ ์ž๋™ ์ƒ์„ฑ ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•˜๊ณ , ๊ฐœ์„  ์—ฌ๋ถ€ ๋ฐ ์ •๋„์— ๋Œ€ํ•œ ์ง€๊ฐ ํ‰๊ฐ€๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜์˜€์„ ๋•Œ ํ•™์Šต์ž ๋ณธ์ธ์˜ ๋ชฉ์†Œ๋ฆฌ๋ฅผ ์œ ์ง€ํ•œ ์ฑ„ ๊ต์ •๋œ ๋ฐœ์Œ์œผ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๋ฉฐ, ์ „ํ†ต์ ์ธ ๋ฐฉ๋ฒ•์ธ ์Œ๋†’์ด ๋™๊ธฐ์‹ ์ค‘์ฒฉ๊ฐ€์‚ฐ (Pitch-Synchronous Overlap-and-Add) ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋น„ํ•ด ์ƒ๋Œ€ ๊ฐœ์„ ๋ฅ  16.67%์ด ํ™•์ธ๋˜์—ˆ๋‹ค.Chapter 1. Introduction 1 1.1. Motivation 1 1.1.1. An Overview of CAPT Systems 3 1.1.2. Survey of existing Korean CAPT Systems 5 1.2. Problem Statement 7 1.3. Thesis Structure 7 Chapter 2. Pronunciation Analysis of Korean Produced by Chinese 9 2.1. Comparison between Korean and Chinese 11 2.1.1. Phonetic and Syllable Structure Comparisons 11 2.1.2. Phonological Comparisons 14 2.2. Related Works 16 2.3. Proposed Analysis Method 19 2.3.1. Corpus 19 2.3.2. Transcribers and Agreement Rates 22 2.4. Salient Pronunciation Variations 22 2.4.1. Segmental Variation Patterns 22 2.4.1.1. Discussions 25 2.4.2. Phonological Variation Patterns 26 2.4.1.2. Discussions 27 2.5. Summary 29 Chapter 3. Correlation Analysis of Pronunciation Variations and Human Evaluation 30 3.1. Related Works 31 3.1.1. Criteria used in L2 Speech 31 3.1.2. Criteria used in L2 Korean Speech 32 3.2. Proposed Human Evaluation Method 36 3.2.1. Reading Prompt Design 36 3.2.2. Evaluation Criteria Design 37 3.2.3. Raters and Agreement Rates 40 3.3. Linguistic Factors Affecting L2 Korean Accentedness 41 3.3.1. Pearsons Correlation Analysis 41 3.3.2. Discussions 42 3.3.3. Implications for Automatic Feedback Generation 44 3.4. Summary 45 Chapter 4. Corrective Feedback Generation for CAPT 46 4.1. Related Works 46 4.1.1. Prosody Transplantation 47 4.1.2. Recent Speech Conversion Methods 49 4.1.3. Evaluation of Corrective Feedback 50 4.2. Proposed Method: Corrective Feedback as a Style Transfer 51 4.2.1. Speech Analysis at Spectral Domain 53 4.2.2. Self-imitative Learning 55 4.2.3. An Analogy: CAPT System and GAN Architecture 57 4.3. Generative Adversarial Networks 59 4.3.1. Conditional GAN 61 4.3.2. CycleGAN 62 4.4. Experiment 63 4.4.1. Corpus 64 4.4.2. Baseline Implementation 65 4.4.3. Adversarial Training Implementation 65 4.4.4. Spectrogram-to-Spectrogram Training 66 4.5. Results and Evaluation 69 4.5.1. Spectrogram Generation Results 69 4.5.2. Perceptual Evaluation 70 4.5.3. Discussions 72 4.6. Summary 74 Chapter 5. Integration of Linguistic Knowledge in an Auxiliary Classifier CycleGAN for Feedback Generation 75 5.1. Linguistic Class Selection 75 5.2. Auxiliary Classifier CycleGAN Design 77 5.3. Experiment and Results 80 5.3.1. Corpus 80 5.3.2. Feature Annotations 81 5.3.3. Experiment Setup 81 5.3.4. Results 82 5.4. Summary 84 Chapter 6. Conclusion 86 6.1. Thesis Results 86 6.2. Thesis Contributions 88 6.3. Recommendations for Future Work 89 Bibliography 91 Appendix 107 Abstract in Korean 117 Acknowledgments 120Docto

    The Acquisition of English stops by Saudi L2 Learners

    Get PDF
    Researchers have studied voice onset time (VOT) in a number of languages but there is a scarcity of research on the acquisition of VOT of English, particularly by adult Saudi learners, and on the VOT of Saudi Arabic. The current study aims to fill these gaps. At the same time, we aimed to assess whether key claims of Flege's Speech Learning Model (SLM) were supported by this kind of data. 31 adult advanced Saudi learners of English and 60 monolinguals (30 native English and 30 Arabic monolinguals) participated in this study. The VOTs of the voiced and voiceless stops were measured followed by three different vowels, in both isolated word and word in sentence contexts. The results show that the learners produced English voiceless stops with aspiration closer to Arabic than to the higher native English VOT values, and voiced stops with pre-voicing, similar to Arabic, rather than with native English short-lag VOT values. Context had an effect in English but vowel did not, while the reverse was true for the learners and Arabic native speakers. Overall, learners' acquisition was modest despite their level and exposure, in that they overwhelmingly resembled Arabic rather than English native speakers. Several hypotheses based on SLM expectations were not confirmed in an unqualified way. However, support was found for learners' phonetic categories being โ€˜deflectedโ€™ away from both L1 and L2 categories. All three groups produced longer positive VOT for aspirated than unaspirated or voiced plosives. All exhibited VOT increasing across places of articulation, front to back for the voiceless stops, but only English native speakers showed this clearly for the voiced stops. Length of residence in UK and daily use of English did not seem to affect nativelikeness of learner VOT

    A conjecture of singing chinese in italian

    Get PDF
    This research intends to show how Chinese contemporary vocal works can be sung with the western lyrical singing technique, focusing on the pronunciation of the Italian language: The way of dealing with Chinese vowels and consonants in the pronunciation of articulation refers to the rules/principles of that presented in Italian language. The subject was inspired by Dr. A. Hirtโ€™s lecture about singing English like Italians in 2011. In terms of rationality, to convey a sense yet also to approach the maximization of the rules of phonation (vowels) and articulation (consonants), researchers hypothesize that Chinese language (Mandarin) can be pronounced like the Italian language but in the setting of singing. This study will take into consideration from pieces of literature about singing technique to teaching, from viewpoints about articulation (in singing) of performers, to recordings and videos. We Believe itโ€™s necessary to import(impart) knowledge about the singing of Chinese phonetics and linguistics, compared to Italian, the most traditional language for singing and the original language of a considerable number of masterpieces on what regards vocal repertoire,since they have been evolving from two completely families of languages

    A Sound Approach to Language Matters: In Honor of Ocke-Schwen Bohn

    Get PDF
    The contributions in this Festschrift were written by Ockeโ€™s current and former PhD-students, colleagues and research collaborators. The Festschrift is divided into six sections, moving from the smallest building blocks of language, through gradually expanding objects of linguistic inquiry to the highest levels of description - all of which have formed a part of Ockeโ€™s career, in connection with his teaching and/or his academic productions: โ€œSegmentsโ€, โ€œPerception of Accentโ€, โ€œBetween Sounds and Graphemesโ€, โ€œProsodyโ€, โ€œMorphology and Syntaxโ€ and โ€œSecond Language Acquisitionโ€.ย Each one of these illustrates a sound approach to language matters

    The effectiveness of shadowing technique through Disney films in consonant pronunciation

    Get PDF
    ENGLISH: One of the important aspects when speaking in English is the good and correct pronunciation. It is because one's pronunciation can affect the success of communicating. Even so, the difference in sound between English and Indonesian makes it difficult for students. To overcome this, the purpose of this research is to find out whether the use of shadowing techniques can help students improve their consonant pronunciation. The shadowing technique is a method of learning English pronunciation that requires students to shadow or imitate audio from native speakers of the target language, namely English. This research used a quantitative approach with a quasi-experimental design. The data that has been collected came from the pre-test and post-test of 35 8th grade students at SMPN 4 Sumenep, which were divided into experimental and control groups. A total of 70 recordings were obtained from these participants. To determine the effect of using the shadowing technique, the collected data were analyzed using the T-test. The results showed that the significance value on the T-test was 0.016 < 0.05. This means, there is a significant effect on students' consonant pronunciation. In addition, in the posttest it was found that students still had difficulty pronouncing consonants /ส’/(70%), /p/(48%), /ฮธ/(48%), /รฐ/(43%), /z/(35 %), /v/(30%), /r/(19%) (experimental group), and consonants /ส’/(82%), /ฮธ/(82%), /รฐ/(75%), /p/(55%), /v/(55%), /z/(43%), /k/(45%) (control group). Based on the results of the T test and the difference in the percentage between the two groups, it can be concluded that the use of shadowing techniques has a positive and significant effect on improving students' consonant pronunciation. INDONESIA: Salah satu aspek penting saat berbicara menggunakan bahasa Inggris adalah pengucapan yang baik dan benar. Hal ini dikarenakan pengucapan seseorang dapat berpengaruh dalam kesuksesan berkomunikasi. Meski begitu, adanya perbedaan bunyi antara Bahasa Inggris dan Bahasa Indonesia membuat siswa kesulitan. Untuk mengatasi hal tersebut, tujuan penelitian ini ialah untuk mengetahui apakah penggunaan teknik shadowing dapat membantu siswa dalam meningkatkan pengucapan konsonan mereka. Teknik shadowing merupakan metode pembelajaran pengucapan bahasa Inggris yang mengharuskan siswa untuk "membayangi" atau meniru sebuah audio dari penutur bahasa target, yaitu bahasa Inggris. Penelitian ini menggunakan pendekatan kuantitatif dengan desain quasi-eksperimen. Data yang telah dikumpulkan berasal dari pre-test dan post-test 35 siswa kelas 8 di SMPN 4 Sumenep yang terbagi dalam kelompok eksperimen dan kontrol. Didapatkan hasil sejumlah 70 rekaman yang berasal dari partisipan tersebut. Untuk menentukan efektifitas penggunaan teknik shadowing, data yang terkumpul dianalisis menggunakan uji T. Hasil penelitian menunjukan bahwa nilai signifikansi pada uji T-test ialah 0.016<0.05. Hal ini bermakna, terdapat pengaruh signifikan terhadap pengucapan konsonan siswa. Selain itu, pada posttest ditemukan bahwa siswa masih kesulitan saat mengucapkan konsonan /ส’/(70%), /p/(48%), /ฮธ/(48%), /รฐ/(43%), /z/(35%), /v/(30%), /r/(19%) (kelompok eksperimen), dan konsonan /ส’/(82%), /ฮธ/(82%), /รฐ/(75%), /p/(55%), /v/(55%), /z/(43%), /k/(45%) (kelompok control). Berdasarkan hasil uji T dan perbedaan prosentase antara kedua kelompok tersebut, dapat disimpulkan bahwa penggunaan teknik shadowing memiki pengaruh positif dan signifikan dalam meningkatkan pengucapan konsonan siswa. ARABIC: ุฃุญุฏ ุงู„ุฌูˆุงู†ุจ ุงู„ู…ู‡ู…ุฉ ุนู†ุฏ ุงู„ุชุญุฏุซ ุจุงู„ู„ุบุฉ ุงู„ุฅู†ุฌู„ูŠุฒูŠุฉ ู‡ูˆ ุงู„ู†ุทู‚ ุงู„ุฌูŠุฏ ูˆุงู„ุตุญูŠุญ. ู‡ุฐุง ู„ุฃู† ู†ุทู‚ ุงู„ุดุฎุต ูŠู…ูƒู† ุฃู† ูŠุคุซุฑ ุนู„ู‰ ู†ุฌุงุญ ุงู„ุชูˆุงุตู„ . ุฑุบู… ุฐู„ูƒุŒ ุงู„ุงุฎุชู„ุงู ููŠ ุงู„ุตูˆุช ุจูŠู† ุงู„ู„ุบุฉ ุงู„ุฅู†ุฌู„ูŠุฒูŠุฉ ูˆุงู„ุฅู†ุฏูˆู†ูŠุณูŠุฉ ูŠุฌุนู„ ุงู„ุฃู…ุฑ ุตุนุจู‹ุง ุนู„ู‰ ุงู„ุทู„ุงุจ. ู„ู„ุชู†ู…ูŠุฉ ุนู„ู‰ ู‡ุฐุง ุŒ ูุฅู† ุงู„ุบุฑุถ ู…ู† ู‡ุฐู‡ ุงู„ุฏุฑุงุณุฉ ู‡ูˆ ู…ุนุฑูุฉ ู…ุง ุฅุฐุง ูƒุงู† ุงุณุชุฎุฏุงู… ุชู‚ู†ูŠุงุช ุงู„ุธู„ ูŠู…ูƒู† ุฃู† ูŠุณุงุนุฏ ุงู„ุทู„ุงุจ ุนู„ู‰ ุชุญุณูŠู† ู†ุทู‚ ุงู„ุญุฑูˆู ุงู„ุณุงูƒู†ุฉ. ุชู‚ู†ูŠุฉ ุงู„ุธู„ ู‡ูŠ ุทุฑูŠู‚ุฉ ู„ุชุนู„ู… ู†ุทู‚ ุงู„ู„ุบุฉ ุงู„ุฅู†ุฌู„ูŠุฒูŠุฉ ุชุชุทู„ุจ ู…ู† ุงู„ุทู„ุงุจ ุชุธู„ูŠู„ ุฃูˆ ุชู‚ู„ูŠุฏ ุตูˆุช ู…ู† ุงู„ู…ุชุญุฏุซูŠู† ุจุงู„ู„ุบุฉ ุงู„ู‡ุฏูุŒ ูˆู‡ูŠ ุงู„ู„ุบุฉ ุงู„ุฅู†ุฌู„ูŠุฒูŠุฉ. ุชุณุชุฎุฏู… ู‡ุฐู‡ ุงู„ุจุญุซ ู†ู‡ุฌู‹ุง ูƒู…ูŠู‹ุง ุจุชุตู…ูŠู… ุดุจู‡ ุชุฌุฑูŠุจูŠ. ุงู„ุจูŠุงู†ุงุช ุงู„ุชูŠ ุชู… ุฌู…ุนู‡ุง ุฌุงุกุช ู…ู† ุงู„ุงุฎุชุจุงุฑ ุงู„ู‚ุจู„ูŠ ูˆุงู„ุจุนุฏูŠ ู„ุฎู…ุณุฉ ูˆ ุซู„ุงุซูŠู† ุทุงู„ุจู‹ุง ููŠ ุงู„ูุตู„ ุงู„ุซุงู…ู† ููŠ ู…ุฏุฑุณุฉ ุงู„ู…ุชูˆุณุทุฉ ุงู„ุญูƒูˆู…ูŠุฉ ุณูˆู…ุงู†ุจ ูˆุงู„ุชูŠ ุชู… ุชู‚ุณูŠู…ู‡ุง ุฅู„ู‰ ู…ุฌู…ูˆุนุงุช ุชุฌุฑูŠุจูŠุฉ ูˆุถุงุจุทุฉ. ุชู… ุงู„ุญุตูˆู„ ุนู„ู‰ ู…ุง ู…ุฌู…ูˆุนู‡ ูงู  ุชุณุฌูŠู„ุงุช ู…ู† ู‡ุคู„ุงุก ุงู„ู…ุดุงุฑูƒูŠู†. ู„ุชุญุฏูŠุฏ ุชุฃุซูŠุฑ ุงุณุชุฎุฏุงู… ุชู‚ู†ูŠุฉ ุงู„ุชุธู„ูŠู„ ุŒ ุชู… ุชุญู„ูŠู„ ุงู„ุจูŠุงู†ุงุช ุงู„ุชูŠ ุชู… ุฌู…ุนู‡ุง ุจุงุณุชุฎุฏุงู… ุงุฎุชุจุงุฑ ุช. ุฃุธู‡ุฑุช ุงู„ู†ุชุงุฆุฌ ุฃู† ู‚ูŠู…ุฉ ุงู„ู…ุนู†ูˆูŠุฉ ููŠ ุงุฎุชุจุงุฑ " ุช" ูƒุงู†ุช ู ูซู ูกูฆ < ู ูซู ูฅ. ู‡ุฐุง ูŠุนู†ูŠ ุฃู† ู‡ู†ุงูƒ ุชุฃุซูŠุฑ ูƒุจูŠุฑ ุนู„ู‰ ู†ุทู‚ ุงู„ุญุฑูˆู ุงู„ุณุงูƒู†ุฉ ู„ุฏู‰ ุงู„ุทู„ุงุจ. ุจุงู„ุฅุถุงูุฉ ุฅู„ู‰ ุฐู„ูƒ ุŒ ูˆุฌุฏ ููŠ ุงู„ุงุฎุชุจุงุฑ ุงู„ุจุนุฏูŠ ุฃู† ุงู„ุทู„ุงุจ ู…ุง ุฒุงู„ูˆุง ูŠูˆุงุฌู‡ูˆู† ุตุนูˆุจุฉ ููŠ ู†ุทู‚ ุงู„ุญุฑู ุงู„ุณุงูƒู† / /(ูงู ูช)ุŒ /p/(ูคูจูช)ุŒ / /(ูคูจูช)ุŒ / / (ูคูฃูช), /z/(ูฃูฅูช)ุŒ /v/(ูฃู ูช)ุŒ /r/(ูกูฉูช) (ู…ุฌู…ูˆุนุฉ ุชุฌุฑูŠุจูŠุฉ), ูˆุงู„ุญุฑูˆู / /(ูจูขูช)ุŒ / /(ูจูขูช)ุŒ //(ูงูฅูช)ุŒ /p/ (ูฅูฅูช)ูซ /v/ (ูฅูฅูช)ูซ /z/(ูคูฃูช)ุŒ /k/(ูคูฅูช) (ู…ุฌู…ูˆุนุฉ ุงู„ุชุญูƒู…). ุจู†ุงุกู‹ ุนู„ู‰ ู†ุชุงุฆุฌ ุงุฎุชุจุงุฑ "ุช" ูˆุงู„ุงุฎุชู„ุงู ููŠ ุงู„ู†ุณุจุฉ ุงู„ู…ุฆูˆูŠุฉ ุจูŠู† ุงู„ู…ุฌู…ูˆุนุชูŠู† ุŒ ูŠู…ูƒู† ุงู„ุงุณุชู†ุชุงุฌ ุฃู† ุงุณุชุฎุฏุงู… ุชู‚ู†ูŠุงุช ุงู„ุธู„ ู„ู‡ ุชุฃุซูŠุฑ ุฅูŠุฌุงุจูŠ ูˆู‡ุงู… ุนู„ู‰ ุชุญุณูŠู† ุงู„ู†ุทู‚ ุงู„ุณุงูƒู† ู„ุฏู‰ ุงู„ุทู„ุงุจ

    The phonological development of typically developing first language Zulu-speaking children aged 2;6 - 6;5 years : a descriptive cross-sectional study

    Get PDF
    Background: Zulu, one of the eleven official languages in South Africa, is the most spoken language in the country. However, research on children's phonological development in Zulu is minimal. To date there are no published Zulu speech assessments and associated normative data that speech-language pathologists (SLPs) can use to identify children with speech sound disorders who speak this language. Method: This descriptive, cross-sectional study aimed to document the phonological development of thirty-two typically developing first language Zulu-speaking children between 2;6 and 6;5 years. Participants attended school or crรจche in Manguzi, KwaZulu-Natal, and were grouped into six month age categories. A single-word Zulu phonology assessment was developed and used to assess the participants. Assessments were audio recorded, and field transcriptions made using the International Phonetic Alphabet (IPA). Speech development was described in terms of phoneme acquisition, word shape, phonological processes and percentage of vowels (PVC) / consonants correct (PCC). Consonant acquisition was assessed in the penultimate syllable only, according to the structure of Zulu

    Phonetically transparent technique for the automatic transcription of speech

    Get PDF
    • โ€ฆ
    corecore