A Corpus of Writing, Pronunciation, Reading, and Listening by Learners of English as a Foreign Language

Kotani, Katsunori; Takai, Yoshimi; Nanjo, H.; Isahara, Hitoshi

doi:10.5539/elt.v9n9p139

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…The interpretation of this term in literature is a language research based on examples of language use in real life. Literature [19] holds that corpus linguistics is the starting point of language description or the method of verifying language hypotheses based on a corpus. Reference [20] realizes the mining of candidate parallel texts through cross language information retrieval technology, and users use one language to retrieve the required information from the data set expressed in another or more languages.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

[Retracted] Russian Speech Conversion Algorithm Based on a Parallel Corpus and Machine Translation

Zhang

2022

Wireless Communications and Mobile Computing

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The phonetic conversion technology is crucial in the resource construction of Russian phonetic information processing. This paper explains how to build a corpus and the key algorithms that are used, as well as how to design auxiliary translation software and implement the key algorithms. This paper focuses on the “parallel corpus” method of problem solving and the indispensable role of a parallel corpus in Russian learning. This paper examines the foundations, motivations, and methods for using parallel corpora in translation instruction. The main way of using a parallel corpus in the classroom environment is to present data, so that learners can be exposed to a large amount of easily screened bilingual data, and translation skills and specific language item translation can be taught in a concentrated and focused manner. Among them, the creation of a large-scale Russian-Chinese parallel corpus will play an important role not only in improving the translation quality of Russian-Chinese machine translation systems but also in Chinese and Russian teaching as well as other branches of linguistics and translation studies, all of which should be given sufficient attention. This paper proposes the use of automatic speech analysis technology to assist Russian pronunciation learning and designs a Russian word pronunciation learning assistant system with demonstration, scoring, and feedback functions, in response to the shortcomings of pronunciation teaching in Russian teaching in China. It can provide corpus support for gathering a large number of parallel corpora and, in the future, enabling online translation. This system is used for corpus automatic construction, and future corpus automatic construction systems could be built on top of it. The proper application of parallel corpus data will aid in the development of a high-quality autonomous learning and translation teaching environment.

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Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

[Retracted] Russian Speech Conversion Algorithm Based on a Parallel Corpus and Machine Translation

Zhang

2022

Wireless Communications and Mobile Computing

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“…Liu and Han (2015) explained corpora as the combination of a large number of language materials with searching and management software stored in a computer, which could store, classify, retrieve, and deduce common wordings and sentence patterns. Kotani et al (2016) indicated that studentcentered teaching allowed students to apply the language corpus to learn languages, understand the real use of languages better, and organize language models and structures. Redmond and Warren (2014) demonstrated that learners could use the corpus according to their personal demands and find the proper way to use a language, which further proved that teachers were no longer the provider of knowledge.…”

Section: Literature Reviewmentioning

confidence: 99%

The Effect of Internet Corpus Learning on Students’ Japanese Learning Motivations and Learning Effect

Shen

2022

Front. Psychol.

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Information education has been vigorously promoted in various countries, making the application of information technologies in language education popular. The combination of information technologies and Japanese learning can make information technologies a practical tool to promote the thinking and cognitive abilities of students in Japanese learning. Corpus teaching is a kind of information technologies integrated teaching method, which enables students to carry out meaningful Japanese learning and promotes learning performance and learning effect of students. Based on information education, the Japanese learning method under Internet corpus is constructed and applied to practical teaching. This study investigates learning performance and the learning effect of students through a questionnaire. Through the experimental design, Japanese teaching has been conducted on 322 students in a university in Shanghai for 18 weeks (3 h/week) under the experimental Internet corpus. Through the experiment, it is found that various factors affect the Internet corpus learning method, and the linear relationship between the influencing factors is divided. Through the comparison results, it is also found that the Internet corpus teaching method can have a positive impact on the learning performance of students and then promote their learning effect. The application of Internet corpus learning matches the development of text corpus and audio corpus and the support of picture databases. Audio and video corpora can effectively improve the learning performance and the learning effect of students by searching for learning content in the database. Suggestions are put forward that the government should optimize its policies to promote Japanese learning and informal education based on learning performance.

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“…The tasks that were given to the speakers for the spoken data collection varied. Some recorded sentence reading (e.g., Corpus of Writing, Pronunciation, Reading, and Listening by Learners of English as a Foreign Language, Kotani et al, 2016), national spoken English test (the College Learners' Spoken English Corpus, Yang and Wei, 2005), role plays (the Barcelona English Language Corpus, Muñoz, 2006), story description (the Santiago University Learner of English Corpus), and interviews (The Louvain International Database of Spoken English Interlanguage, Gilquin et al, 2010). Some corpora provide transcription of a phonetic level (the LeaP Corpus : Learning Prosody in a Foreign Language, Slavianova, 2007), while some corpora focus on word level transcription (ICNALE: the International Corpus Network of Asian Learners of English, Ishikawa, 2013).…”

Section: Overviewmentioning

confidence: 99%

The Learner Corpora of Spoken English: What Has Been Done and What Should Be Done?

Yoon¹

2020

Lang. Res.

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The number of spoken learner corpora is smaller than that of written corpora; however, demand for spoken corpora has continuously increased. This study investigates the current state of spoken English-language learner corpora both in the world and in Korea, with a focus on their size, speakers, and genres. Based on this survey, the study discusses factors to consider when building and publishing a spoken learner corpus, especially with respect to the issues of conversation genre, proficiency level, and annotation.

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A Corpus of Writing, Pronunciation, Reading, and Listening by Learners of English as a Foreign Language

Cited by 4 publications

References 8 publications

[Retracted] Russian Speech Conversion Algorithm Based on a Parallel Corpus and Machine Translation

[Retracted] Russian Speech Conversion Algorithm Based on a Parallel Corpus and Machine Translation

The Effect of Internet Corpus Learning on Students’ Japanese Learning Motivations and Learning Effect

The Learner Corpora of Spoken English: What Has Been Done and What Should Be Done?

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