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9th International Conference on Intelligent Tutoring Systems

作者： Kulkarni, Anagha Heilman, Michael Eskenazi, Maxine Callan, Jamie Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9783540691303

Words with multiple meanings are a phenomenon inherent to any natural language. In this work, we study the effects of such lexical ambiguities on second language vocabulary learning. We demonstrate that machine learning algorithms for word sense disambiguation can induce classifiers that exhibit high accuracy at the task of disambiguating homonyms (words with multiple distinct meanings). Results from a user study that compared two versions of a vocabulary tutoring system, one that applied word sense disambiguation to support learning and another that did not, support rejection of the null hypothesis that learning outcomes with and without word sense disambiguation are equivalent, with a p-value of 0.001. To our knowledge this is the first work that investigates the efficacy of word sense disambiguation for facilitating second language vocabulary learning.

关键词： vocabulary learning word sense disambiguation English as a second language computer assisted language learning

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XDF-REPA : A Densely Labeled Dataset toward Refined Pronunciation Assessment for English learning 22

XDF-REPA : A Densely Labeled Dataset toward Refined Pronunci...

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22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)

作者： Gao, Yun Ou, Zhigang Cheng, Jianfeng Ruan, Yong Wang, Xiangdong Qian, YueLiang New Oriental Educ & Technol Grp Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728124490

Currently, most computer assisted pronunciation training (CAPT) systems focus on overall scoring or mispronunciation detection. In this paper, we address the issue of refined pronunciation assessment (RPA), which aims at providing more refined information to L2 learners. To meet the major challenge of the lack of densely labeled data, we present the XDF-REPA dataset, which is freely available to the public. The dataset contains 19,213 English word utterances by 18 Chinese adults, among which 4,200 audio clips from 9 speakers are densely labeled by 3 linguists with intended phoneme, actually uttered phoneme, phoneme score for each phoneme, and an overall score for the word as well. To reduce the difference between annotators, scoring rules combining subjectivity and objectivity are defined. To demonstrate the usage of the dataset and provide a baseline for other researchers, a prototype system for RPA is developed and described in the paper, which adopts a DNN-HMM based acoustic model and a variant of Goodness of Pronunciation (GOP) to yield all the corrective feedbacks needed for RPA. Experimental results show error detection accuracy varies from 80.1% to 85.1% for different subsets and linguists, and accuracy of actually-utteredphoneme recognition varies from 70.9% to 80.8% for different subsets and linguists.

关键词： mispronunciation detection and diagnosis refined dataset computer assisted language learning

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Technology on CALL: Improving English language learning in a Spanish Context 13

Technology on CALL: Improving English Language Learning in a...

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13th European Conference on e-learning (ECEL)

作者： Segura-Harvey, Beatrice Greener, Sue Univ Brighton Brighton BN2 4AT E Sussex England

ISBN: (纸本)9781910309698

The acquisition of English as a second language remains a vital necessity for business in a globalized environment. Once a particularly early pioneer of e-learning, second language acquisition has not moved with current thinking on learning and rapid technological advances in terms of platforms and devices. The focus of this paper is a much needed review of "computer assisted language learning (CALL)" with recommendations for continued research and development applied to a Spanish context. With the recent economic crisis in the Spanish economy, due to global economic pressures from 2008, there has been a dramatic drop in employment, which consequently has forced Spanish citizens to leave the country looking for work. However, the variable quality of language teaching and learning in schools has produced a deficit in skilled workers and professionals with a suitable level of working English. These two areas of change, CALL and Spain's employability issues, mean that businesses and language academies have to tackle the deficit. This paper describes research into the potential benefits and difficulties faced by businesses and individual learners in improving English language acquisition and aims to determine whether improved use of technology could help. The global use of CALL was investigated and, within this context, research was conducted in Spain with learners of English and language academy directors to analyse the environment of computer-assisted language learning within Spain. This was a cross-sectional study using mixed methods for the purposes of triangulation of data: following a review of relevant literature, the results of a student survey and a management survey were analysed and used to develop realistic online lessons with Spanish students to test out the concepts identified in the research. The outcomes of this case study are also presented in the paper, although at this stage of the research only a very limited test has been possible. The study has foc

关键词： computer assisted language learning employability attitudes towards technology Spain

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Technology-enhanced collaborative language learning: theoretical foundations, technologies, and implications

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computer assisted language learning 2022年第8期35卷 1754-1788页

作者： Su, Fan Zou, Di Educ Univ Hong Kong Dept English Language Educ Hong Kong Peoples R China

With the emergence of educational technology, technology-enhanced collaborative language learning had gained increasing attention from learners, educators, and researchers, and a large number of studies had been conducted to investigate the effects of technology-enhanced collaborative learning on students' development of language knowledge and affective status. However, little comprehensive review that investigated all aspects of the field thoroughly had been conducted, and the present research was an attempt in response to this call. Specifically, this research reviewed 40 articles on technology-enhanced collaborative language learning from five aspects, (1) the nature of publications, (2) the theoretical frameworks of the previous research, (3) the types of the technologies for collaborative language learning, (4) the effectiveness of the technologies, and (5) the implications of the studies. The results showed 10 theoretical frameworks, nine types of technologies, and 11 benefits of technology-enhanced collaborative language learning. Important implications were also discussed for future design and implementation of technology-enhanced collaborative language learning activities.

关键词： Collaborative learning computer assisted language learning educational technology mobile assisted language learning

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An Effective CALL System for Strongly Accented Mandarin Speech

An Effective CALL System for Strongly Accented Mandarin Spee...

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International Conference on Research Challenges in computer Science

作者： Jiang, Tonghai Tang, Ming Ge, Fengpei Liu, Changliang Dong, Bin Chinese Acad Sci Xinjiang Tech Inst Phys & Chem Urumqi Peoples R China Xinjiang Publ Secur Dept Urumqi Peoples R China Chinese Acad Sci Inst Acoust ThinkIT Speech Lab Beijing Peoples R China

ISBN: (纸本)9780769539270

In this paper, we investigate some specific acoustic problems of the computer assisted language learning (CALL) system by modifying the acoustic model and feature under the speech recognition framework. At first, in order to alleviate the distortion of channel and speaker, speaker-dependent Cepstrum Mean Normalization (Speaker CMN) is adopted, by which the average correlation coefficient (ACC) between human and machine scores is improved from 78.00% to 84.14%. Then, Heteroscedastic Linear Discriminate Analysis (HLDA) is applied to enhance the discrimination ability of acoustic model, which successfully increases ACC from 84.14% to 84.62%. Additionally, HLDA can lessen the great human-machine scoring difference of speeches that have very good or too bad quality, and so leads to an increase of the correctly-rank rate from 85.59% to 90.99%. Finally, we use the technology of Maximum a Posteriori (MAP) to tune the acoustic model to match the strongly accented testing speech. As the result, ACC is improved from 84.62% to 86.57%.

关键词： computer assisted language learning Pronunciation Quality Assessment HLDA Speaker CMN MAP

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Effect of Multimedia Annotation System on Improving English Writing and Speaking Performance

Effect of Multimedia Annotation System on Improving English ...

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5th International Conference on E-learning and Games, Edutainment 2010

作者： Hwang, Wu-Yuin Shadiev, Rustam Huang, Szu-Min Natl Cent Univ Grad Inst Network Learning Technol Jhongli 32001 Taoyuan County Taiwan

ISBN: (纸本)9783642145322

In this study learning activities were designed with the focus on students English writing and speaking performance The Virtual Pen (VPen) multimedia web annotation system were provided to help student participate at learning activities by cleating annotations sharing them and giving feedback to peers work One experiment was conducted with VPen in an English class for a period of one semester and the following results were obtained Students per cerved VPen as easy to use useful during participation at learning activities and students had positive attitude toward using VPen Besides students found designed activities is useful in improving their writing and speaking performance and playful Furthermore students' actual VPen usage had significant correlation with speaking and writing performance Further investigation demonstrated that students speaking and wilting performance significantly correlated with learning achievement Based on out finding we conclude that learning activities designed in this study with VPen system employed facilitate students writing and speaking skill and therefore improve their learning achievement

关键词： computer assisted language learning Virtual Pen Playfulness language Productive Skills

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P-AWL: Academic Word List for Portuguese

P-AWL: Academic Word List for Portuguese

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9th International Conference on Computational Processing of the Portuguese language

作者： Baptista, Jorge Costa, Neuza Guerra, Joaquim Zampieri, Marcos Cabral, Maria Mamede, Nuno Univ Algarve Campus Gambelas P-8005139 Faro Portugal INESC ID Lisboa Spoken Language Lab P-1000029 Lisbon Portugal

ISBN: (纸本)9783642123191

This paper presents and discusses the methodology for the construction of an Academic Word List for Portuguese: PAWL, inspired in its English equivalent. The aim of this linguistic resource is to provide a solid base for future studies and applications on computer assisted language learning, while maintaining comparability with other comparable resources.

关键词： Portuguese academic word list computer assisted language learning

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Self-assessment of Motivation: Explicit and Implicit Indicators in L2 Vocabulary learning

Self-assessment of Motivation: Explicit and Implicit Indicat...

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15th International Conference on Artificial Intelligence in Education (AIED)

作者： Dela Rosa, Kevin Eskenazi, Maxine Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9783642218682;9783642218699

Self-assessment motivation questionnaires have been used in classrooms yet many researchers find only a weak correlation between answers to these questions and learning. In this paper we postulate that more direct questions may measure motivation better, and they may also be better correlated with learning. In an eight week study with ESL students learning vocabulary in the REAP reading tutor, we administered two types of self-assessment questions and recorded indirect measures of motivation to see which factors correlated well with learning. Our results showed that some user actions, such as dictionary look up frequency and number of times a word is listened to, correlate well with self-assesment motivation questions as well as with how well a student performs on the task. We also found that using more direct self-assesment questions, as opposed to general ones, was more effective in predicting how well a student is learning.

关键词： Motivation Modelling Intelligent Tutoring Systems computer assisted language learning Motivation Diagnosis English as a Second language

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ASR inspired syllable stress detection for pronunciation evaluation without using a supervised classifier and syllable level features 20

ASR inspired syllable stress detection for pronunciation eva...

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Interspeech Conference

作者： Ramanathi, Manoj Kumar Yarra, Chiranjeevi Ghosh, Prasanta Kumar Indian Inst Sci IISc Elect Engn Bangalore 560012 Karnataka India

Automatic syllable stress detection is typically performed with a supervised classifier considering manually annotated stress markings and features computed within the syllable segments derived from phoneme transcriptions and their time-aligned boundaries. However, the manual annotation is tedious and the errors in estimating segmental information could degrade stress detection accuracy. In order to circumvent these, we propose to estimate stress markings in automatic speech recognition (ASR) framework involving finite-state-transducer (FST) without using annotated stress markings and segmental information. For this, we train the ASR system with native English data along with pronunciation lexicon containing canonical stress markings and decode non-native utterances as pronunciations embedded with stress markings. In the decoding, we use an FST encoded with the pronunciations derived using phoneme transcriptions and the instructions involved in a typical manual annotation. Experiments are conducted on polysyllabic words taken from ISLE corpus containing utterances spoken by Italian and German speakers and using the ASR models trained with three corpora. Among all the three models, the highest stress detection accuracies with the proposed approach respectively on Italian & German speakers are found to be 2.07% & 1.19% higher than and comparable to those with the two supervised classification approaches used as baselines.

关键词： Syllable stress detection unsupervised approach computer assisted language learning ASR inspired modeling

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A UNIVERSAL ORDINAL REGRESSION FOR ASSESSING PHONEME-LEVEL PRONUNCIATION 47

A UNIVERSAL ORDINAL REGRESSION FOR ASSESSING PHONEME-LEVEL P...

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47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Mao, Shaoguang Soong, Frank Xia, Yan Tien, Jonathan Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9781665405409

The efficacy and robustness of Ordinal Regression (OR) in assessing speech pronunciation for language learning at phrase level has been shown before. However, for assessing phoneme pronunciation, we need to: 1. collect human scoring annotations for phoneme tokens of a short duration (60-70 ms);2. train an ordinal regression model for each phoneme with the corresponding training and inference costs. In this paper, we propose to train a Universal Ordinal Regression (UOR) model instead of multiple, separate models for different phonemes, and evaluate its performance accordingly. A single universal binary classifier in UOR is trained to make a binary preference decision (better or worse) between a pair of two tokens with the same phoneme ID. In inference, labeled anchored tokens of specific phoneme ID in the training data are paired with test phoneme token to make binary preference decisions. By evaluating the new UOR on Speechocean762, a public speech database for pronunciation evaluation, we show the advantages of the proposed new approach. Improvements of Pearson Correlation Coefficient by 16.7% and Mean Square Error by 25.0%, all relatively, are obtained against the state-of-the-art systems.

关键词： computer assisted language learning Universal Ordinal Regression Pronunciation Assessment Mispronunciation Detection

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