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Artículos de revistas sobre el tema "Spoken English"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Ramesh, S., and M. Suresh Kumar. "Teaching Spoken English." Journal of Advances and Scholarly Researches in Allied Education 15, no. 9 (2018): 34–36. http://dx.doi.org/10.29070/15/57913.

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2

Heptonstall, G. "Spoken/Broken." English 46, no. 184 (1997): 60–61. http://dx.doi.org/10.1093/english/46.184.60.

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3

Rodriguez, Fatima, Sandra E. Echeverria, Sri Ram Pentakota, Chioma Amadi, Katherine G. Hastings, and Latha P. Palaniappan. "Comparison of Ideal Cardiovascular Health Attainment and Acculturation among Asian Americans and Latinos." Ethnicity & Disease 29, no. 2 (2019): 287–96. http://dx.doi.org/10.18865/ed.29.2.287.

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Objective: To determine the association between language and ideal cardiovascular health among Asian Americans and Latinos.Design/ Study Participants: Cross-sectional study using 2011-2016 National Health and Nutrition Examination Survey of Asian Americans (n=2,009) and Latinos (n=3,906).Interventions: Participants were classified according to language spoken at home (only/mostly English spoken, both English and native language spoken equally, or mostly/only native language spoken).Outcomes: Ideal, intermediate and poor cardiovascular health status for smoking, blood pressure, glucose level, a

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4

Mayes, Patricia. "Quotation in Spoken English." Studies in Language 14, no. 2 (1990): 325–63. http://dx.doi.org/10.1075/sl.14.2.04may.

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5

Kolesnikova, Olga, and Oscar-Arturo González-González. "Spoken English Learner Corpora." Research in Computing Science 130, no. 1 (2016): 111–32. http://dx.doi.org/10.13053/rcs-130-1-10.

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6

Calude, Andreea S., and Gerald P. Delahunty. "Inferentials in spoken English." Pragmatics. Quarterly Publication of the International Pragmatics Association (IPrA) 21, no. 3 (2011): 307–40. http://dx.doi.org/10.1075/prag.21.3.02cal.

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Although there is a growing body of research on inferential sentences (Declerck 1992, Delahunty 1990, 1995, 2001, Koops 2007, Pusch 2006), most of this research has been on their forms and functions in written discourse. This has left a gap with regards to their range of structural properties and allowed disagreement over their analysis to linger without a conclusive resolution. Most accounts regard the inferential as a type of it-cleft (Declerck 1992, Delahunty 2001, Huddleston and Pullum 2002, Lambrecht 2001), while a few view it as an instance of extraposition (Collins 1991, Schmid 2009). M

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7

Gao, Chi. "The Spoken English Practice System Based on Computer English Speech Recognition Technology." Mobile Information Systems 2022 (April 6, 2022): 1–11. http://dx.doi.org/10.1155/2022/9033421.

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Spoken English practice requires a combination of listening, speaking, reading, and writing, among which listening and speaking are the most difficult. In order to improve the speaking ability of the practitioner, the pronunciation of spoken English needs to be corrected in time. However, the workload of manual evaluation is too large, so it is necessary to combine intelligent methods for spoken language recognition. Based on the needs of spoken English pronunciation correction, this paper combines the computer English speech recognition technology to construct the spoken English recognition a

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8

Peng, Yong Mei, and Yun Hua Qu. "Based on Research Connecting Word Corpus of Spoken English." Advanced Materials Research 1030-1032 (September 2014): 2689–92. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.2689.

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This paper examines our spoken English Majors used to connect words and characteristics. Corpus used the "Chinese students Spoken and Written English Corpus (SWECCL2.0)" in the spoken corpus SECCL2.0, reference corpus used in the British National Corpus BNC spoken corpus BNC Spoken Corpus (BNC / S). The study found that of native speakers of English majors and English spoken words using both common connections are also differences. Meanwhile, China's English Majors spoken word there are multiple connections with the situation misuse. Based on the findings, the article on spoken English teachin

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9

Umarov, Bobur Norboevich. "THE MAIN METHODS OF ANALYSIS OF WRITTEN AND SPOKEN ENGLISH." EURASIAN JOURNAL OF ACADEMIC RESEARCH 2, no. 2 (2022): 572–75. https://doi.org/10.5281/zenodo.6327482.

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Many differences between written English and spoken English can be clearly distinguished, as there are many elements in which a clear contrast can be observed. Written English is the English that is referred to in texts and other similar material. Spoken language is what a person hears and uses to communicate with others. While both written and spoken language can be used as a means of communication, the key difference between written and spoken English is that written English is text-based and spoken English is not. In this article, let's look at the differences between these two types wi

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10

Huang, Lihua. "An Improved BP Deep Neural Network Multimedia Used in Oral English Training." Scientific Programming 2022 (January 31, 2022): 1–11. http://dx.doi.org/10.1155/2022/8995398.

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In order to improve the effect of spoken English training, this paper combines multimedia information technology to reform the teaching of spoken English training, and integrates BP neural network English into spoken English training. Moreover, this paper combines the actual needs of spoken English training and the teaching framework of the multimedia system to construct the data set, clean up the data set, and implement the word vector representation of students and professionals. In addition, this paper constructs the entire system framework of the spoken English resource recommendation algo

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11

Tao, Hui, and Zhe Zhang. "Self-Study System Assessment of Spoken English considering the Speech Scientific Computing Knowledge Assessment Algorithm." Wireless Communications and Mobile Computing 2022 (May 26, 2022): 1–13. http://dx.doi.org/10.1155/2022/3305499.

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For the purpose of effectively improving the assessment accuracy of spoken English self-study quality of English learners, a speech scientific computing knowledge assessment algorithm is introduced into the assessment of the self-study system of spoken English. Through the combination of spoken English speech assessment and accuracy detection, a DSP-based self-study assessment system for spoken English is designed. This system is mainly divided into two parts: voice signal processing and hardware circuit design. The features of spoken English self-study speech are extracted based on the multil

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12

Zhan, Xia. "A Convolutional Network-Based Intelligent Evaluation Algorithm for the Quality of Spoken English Pronunciation." Journal of Mathematics 2022 (January 18, 2022): 1–9. http://dx.doi.org/10.1155/2022/7560033.

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Aiming at the problems of long time consumption and low accuracy of traditional spoken English pronunciation quality assessment algorithms, a convolutional network-based intelligent assessment algorithm for spoken English pronunciation quality is proposed. The convolutional neural network structure is given, the original data of the spoken English pronunciation voice signal are collected by multisensor detection, and the spoken English pronunciation voice signal model is constructed. Based on audio and convolutional neural network learning and training, it realizes the feature selection and cl

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13

Wober, Mallory. "English - as she ain't spoken." British Journalism Review 8, no. 2 (1997): 64–67. http://dx.doi.org/10.1177/095647489700800210.

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14

Boberg, Charles. "Describing Spoken English: An Introduction." Journal of English Linguistics 28, no. 1 (2000): 96–99. http://dx.doi.org/10.1177/00754240022004811.

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15

Thomison, John B. "English As She Is Spoken." Southern Medical Journal 82, no. 9 (1989): 1069–70. http://dx.doi.org/10.1097/00007611-198909000-00001.

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16

Stewart, Ralph. "A decline in spoken English?" English Today 19, no. 3 (2003): 57–58. http://dx.doi.org/10.1017/s0266078403003110.

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“THIS IS THE CBC,” says the announcer. Till quite recently, stressing the “is” would have implied that someone had been asserting that it WASN'T the Canadian Broadcasting Company, but not now. Similarly, we are told that the Olympic games ARE taking place, tomorrow WILL be sunny, and the host of the program HAS convened the usual panel.

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17

Ciliberti, Anna. "Spoken English: A practical guide." Journal of Pragmatics 16, no. 6 (1991): 591–96. http://dx.doi.org/10.1016/0378-2166(91)90103-5.

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18

House, Jill. "Prosodic patterns in spoken English." Computer Speech & Language 2, no. 3-4 (1987): 364–67. http://dx.doi.org/10.1016/0885-2308(87)90019-2.

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19

Bao, Shijun. "Design of Digital Teaching Platform for Spoken English Based on Virtual Reality." Advances in Multimedia 2022 (August 28, 2022): 1–10. http://dx.doi.org/10.1155/2022/3274852.

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In order to improve the effect of digital teaching of spoken English, this paper combines virtual reality technology to design a digital teaching platform for spoken English and combines virtual reality technology to digitally process spoken English. The signal processed by the front-end amplifier circuit is converted into a digital signal through analog-to-digital conversion, and the digital receiving system is realized by means of software radio, which reduces the dependence on the hardware circuit and enhances the portability of the system. In addition, this paper selects filters according

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20

Teh, June Li, and Zahariah Pilus. "International students’ perspectives of Malaysian English teachers’ spoken English." Indonesian Journal of Applied Linguistics 8, no. 3 (2019): 554. http://dx.doi.org/10.17509/ijal.v8i3.15255.

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Numerous studies comparing native and non-native English teachers have found that ESL students prefer native teachers for teaching speaking skills and pronunciation. In other words, non-native teachers are viewed as less superior in matters related to spoken language. This study explores international students’ views on spoken English of Malaysian teachers in English language classrooms. 81 international students who were attending English language classes as a preparation for university programmes at a Malaysian university participated in the study. The students were given a short writing tas

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21

Li, Shuning. "The Challenges and Dilemmas of Spoken English Education in the Context of the Compulsory Education System in China." Transactions on Social Science, Education and Humanities Research 11 (August 20, 2024): 629–36. http://dx.doi.org/10.62051/w3r18869.

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Many students in China are disturbed by their inability to speak English fluently, and "dumb English" is a common phenomenon among English learners in China. There are some problems in spoken English education in the elementary education stage in China, which to a certain extent have led to the formation of this phenomenon. Taking English education in China's compulsory education stage as the background, this study conducted semi-structured interviews with four front-line English teachers in primary and junior high schools to gain an in-depth understanding of the current situation of English e

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22

Min, Sujung. "Comment Markers in Spoken English in Korea." English Teachers Association in Korea 30, no. 2 (2024): 1–17. http://dx.doi.org/10.35828/etak.2024.30.2.1.

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The present study examines the use of four categories of comment markers among Korean speakers of English, a category of grammatical items whose use is prompted by pragmatic factors, using the data from the elicited conversation in English. Previous research on comment markers has suggested that comment markers are more frequent in the Inner Circle varieties than in the Outer Circle varieties and that there are systematic differences in the distribution of comment markers between Kachru’s Inner and Outer Circles. Since English is learned and used as an important foreign language in Korea, Kore

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23

Liu, Yang, and Jianguo Tian. "Error Analysis of College Students’ Spoken English." International Journal of Languages, Literature and Linguistics 7, no. 4 (2021): 182–88. http://dx.doi.org/10.18178/ijlll.2021.7.4.309.

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Based on the theory of Error Analysis, this thesis records the production of spoken English of first year college students of Northwestern Polytechnical University as samples. After listening to the recorder repeatedly and carefully, the author classifies and describes the errors found in the corpus, investigates the causes of these errors and provides solutions to these problems. It is found that there are errors of performance, phonological errors, lexical errors, grammatical errors and pragmatic errors in this study. Reasons for these errors can be explained from the perspectives of interli

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24

Jin, Yanju. "Design of Students’ Spoken English Pronunciation Training System Based on Computer VB Platform." International Journal of Emerging Technologies in Learning (iJET) 14, no. 06 (2019): 41. http://dx.doi.org/10.3991/ijet.v14i06.10154.

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Spoken English communication is most commonly used in the international communication. However, the accuracy of spoken English pronunciation is the key factor to restrict English learners in China. For the current situation that spoken English proficiency is generally low in China, this paper aims to design a spoken English pronunciation training system that will provide guidance and help for English learners’ spoken pronunciation. The Visual Basic platform is used in the design of the system. This paper first conducts an in-depth study on the related theories of voice recognition, discusses t

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25

Sadeghi, Karim, and Jack C. Richards. "Teaching spoken English in Iran’s private language schools: issues and options." English Teaching: Practice & Critique 14, no. 2 (2015): 210–34. http://dx.doi.org/10.1108/etpc-03-2015-0019.

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Purpose – Mastery of spoken English is a priority for many learners of English in Iran. Opportunities to acquire spoken English through the public school system are very limited, hence many students enroll in “conversation” courses in private institutes. The purpose of this paper is to report a study of how institute teachers address the teaching of spoken English. Design/methodology/approach – Eighty-nine teachers completed a questionnaire on how they teach spoken English. The information was supplemented with interviews and classroom observation. Findings – Results suggest that institute cou

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26

Zhu, Min. "The Application of Intelligent Speech Analysis Technology in the Spoken English Language Learning Model." Mobile Information Systems 2022 (May 9, 2022): 1–11. http://dx.doi.org/10.1155/2022/3192892.

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In order to improve the effect of spoken English processing, it is necessary to improve the spoken English processing technology from the perspective of the characteristics of spoken English, combined with intelligent algorithms. This paper combines the intelligent speech analysis technology to improve the spoken English recognition technology and combines the actual and needs of English learning to improve the system algorithm. Moreover, this paper combines the intelligent speech analysis to construct the intelligent spoken English learning model structure and combines the statistical method

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27

Johnson, Jeanne M., Ruth V. Watkins, and Mabel L. Rice. "Bimodal bilingual language development in a hearing child of deaf parents." Applied Psycholinguistics 13, no. 1 (1992): 31–52. http://dx.doi.org/10.1017/s0142716400005415.

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ABSTRACTThis study examined the spoken English development of a hearing child of deaf parents who used American Sign Language (ASL). The child first learned ASL in interactions with his parents and later developed spoken English outside the home environment. It was hypothesized that the child's acquisition of spoken English would systematically reflect both expected monolingual developmental patterns and interlinguistic transfer. Four areas of mismatch between ASL and spoken English were identified. Language sample data from ages 2;9–5;2 were examined for evidence to evaluate the hypotheses. F

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Ren, Junlong. "Study on Automatic Evaluation Method of Spoken English Based on Multimodal Discourse Analysis Theory." Security and Communication Networks 2021 (December 27, 2021): 1–8. http://dx.doi.org/10.1155/2021/1486575.

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Aiming at the low confidence of traditional spoken English automatic evaluation methods, this study designs an automatic evaluation method of spoken English based on multimodal discourse analysis theory. This evaluation method uses sound sensors to collect spoken English pronunciation signals, decomposes the spoken English speech signals by multilayer wavelet feature scale transform, and carries out adaptive filter detection and spectrum analysis on spoken English speech signals according to the results of feature decomposition. Based on multimodal discourse analysis theory, this evaluation me

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Wang, Liyan, Jun Yang, Yongshan Wang, Yong Qi, Shuai Wang, and Jian Li. "Integrating Large Language Models (LLMs) and Deep Representations of Emotional Features for the Recognition and Evaluation of Emotions in Spoken English." Applied Sciences 14, no. 9 (2024): 3543. http://dx.doi.org/10.3390/app14093543.

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This study is dedicated to developing an innovative method for evaluating spoken English by integrating large language models (LLMs) with effective space learning, focusing on the analysis and evaluation of emotional features in spoken language. Addressing the limitation of current spoken English evaluation software that primarily focuses on acoustic features of speech (such as pronunciation, frequency, and prosody) while neglecting emotional expression, this paper proposes a method capable of deeply recognizing and evaluating emotional features in speech. The core of the method comprises thre

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Dr., A. John Lawrence. "WHY DO THE L2 STUDENTS STRUGGLE TO SPEAK ENGLISH PROPERLY?" International Journal of Multidisciplinary Research and Modern Education (IJMRME) 7, no. 1 (2021): 1–4. https://doi.org/10.5281/zenodo.4431115.

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The descriptive survey research aims at exploring why the students struggle to speak English properly without mistakes even after years of learning English at schools and completing their graduation studies, from students’ perspective.The study is conducted on 182 B.Ed. students taken from two colleges of education in India.The investigator used a self-constructed and validated Questionnaire for the study. 11 questions were asked and the results were analysed. The findings of the study reveal that majority of the students were not are able to speak in English without mistakes [Research Q

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Zhang, Menglin, Xiaoshu Xu, and YunFeng Zhang. "The Impact of Personal Learning Environments on Chinese Junior High School Students' Spoken English Narrative Competence." International Journal of Virtual and Personal Learning Environments 13, no. 1 (2023): 1–23. http://dx.doi.org/10.4018/ijvple.329599.

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This study designed and implemented a personal learning environment platform for spoken English teaching in a junior high school in China to improve students' spoken English narrative competence. Altogether, 83 junior high school year one students took part in this study. The participants were divided into experimental and control classes for the two-month-long experiment. The personal learning environment-based spoken English platform was implemented in the experimental class, while the control class used traditional face-to-face instruction. Pre- and post-spoken English tests and semistructu

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Han, Mengqing, and Shanshan Niu. "Application of Virtual Scenario Teaching in Spoken English Teaching." International Journal of Emerging Technologies in Learning (iJET) 16, no. 18 (2021): 129. http://dx.doi.org/10.3991/ijet.v16i18.25659.

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The ultimate goal of learning the English language is oral communication. Virtual scenario teaching (VST) provides the speaking and listening opportunities for learners of spoken English, and allows students to actively participate in the creation of an English environment. Based on VST, this paper summarizes the status quo of spoken English teaching, applies VST to the teaching of spoken English, and evaluates the teaching effect. The results show that VST enhances the students’ ability of language expression, and stimulates their learning interest. With the aid of VST, students can master re

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Wang, Yongjuan, and Peng Zhao. "A Probe into Spoken English Recognition in English Education Based on Computer-Aided Comprehensive Analysis." International Journal of Emerging Technologies in Learning (iJET) 15, no. 03 (2020): 223. http://dx.doi.org/10.3991/ijet.v15i03.12937.

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At present, computer-aided spoken English learning is becoming increasingly popular among learners. The computer-aided comprehensive analysis tech-nology can evaluate and correct learner's spoken pronunciation, thereby im-proving their pronunciation. Based on computer-aided comprehensive analy-sis, this paper aims to explore the automatic recognition and scoring methods of spoken English in English education. For this, it studies the effective matching of the feedback information with the known pronunciation scoring results, and then develops a computer evaluation plug-in consisting of dif-fer

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H. Narendra Kumar, M. Tilak,, B. Mohan Teja,, and S. Santha Kumari. "New Challenges In Teaching Spoken English For Employment At The Undergraduate Level." Journal of Namibian Studies : History Politics Culture 33 (May 16, 2023): 3258–67. http://dx.doi.org/10.59670/jns.v33i.5079.

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The employment sector in India is diversifying with the liberalization of the economy. Education at the undergraduate level is however at present, not in tune with the requirements of the job market. In order to provide employment related skills to the undergraduate students, more stress needs to be placed on linking education with work. This is applicable to the teaching of Spoken English also. This paper addresses the need to give more importance to the development of the speaking skills in English, which is the most neglected skill among the language skills taught at the undergraduate

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Jiang, Zhaoxia. "Spoken English Assessment Using Confused Phoneme Assessment Model." Mobile Information Systems 2021 (May 28, 2021): 1–10. http://dx.doi.org/10.1155/2021/2574332.

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Under normal circumstances, in the process of evaluating the phoneme of spoken English which is easy to be confused, it is impossible to accurately assess the oral ability of different groups of people according to their oral ability. The assessment process has problems of poor robustness and low stability. We propose a spoken English assessment method based on an easily confused phoneme assessment model to address these problems. We design an English easily confused phoneme-based evaluation model in the proposed framework by adopting fuzzy logic for the assessment task. We also present HPD se

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Liu, Yijun. "Differences between Spoken and Written English." Communications in Humanities Research 3, no. 1 (2023): 766–70. http://dx.doi.org/10.54254/2753-7064/3/20220615.

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The link between spoken and written language has been the subject of many diverse perspectives throughout the history of language research. Many linguists considered written language a variant of spoken language in the past few decades. But over time, written language has come to hold a dominant position. Therefore, this paper reviews the differences between the two types of English language, spoken and written English, by analyzing the features of these two types of English through three aspects: production and perception, forms, and formality. This review also provides some pedagogical sugge

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Ridwan, Rina Indrianty, Ahmad Munir, and Oikurema Purwati. "THE PERCEPTION ABOUT DIFFICULTIES OF DIALECT BUGINESE TOWARD STUDENT’S SPEAKING IN MUHAMMADIYAH UNIVERSITY OF MAKASSAR." EXPOSURE : JURNAL PENDIDIKAN BAHASA INGGRIS 11, no. 1 (2022): 100–115. http://dx.doi.org/10.26618/exposure.v11i1.6732.

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The difficulty of speaking English, especially for first graders It will be a sustainable issue. Seeing that phenomenon, this study aimed to see difficulty in speaking English among first graders of English education Muhammadiyah University of Makassar. There are two in this study. This study takes a qualitative approach of choosing a location and choosing Students will batch 2020 as a participant in this study. Participants were selected through recommendations from all instructors who taught the course. About difficulty in speaking English, 4 difficulties in this study. The result was Interf

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Rayah, Rabiatul Adawiyah, Nurul Aiman Mohd Jafre, Nor Aini Husain, and Wan Rosedayu Wan Mohamad Nawawi. "Attitude and motivation in spoken English." Jurnal EDUCATIO: Jurnal Pendidikan Indonesia 4, no. 2 (2018): 100. http://dx.doi.org/10.29210/120182256.

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<p><em>English language proficient has currently becoming a necessary requirement in various fields of study and professions. However, most students refuse to speak in English because they are too concerned in making mistakes, lack of motivation, and low self-confidence. In learning English, attitude and motivation are very closely related. A learner with positive attitude towards learning a language has a high tendency of motivation towards it. Therefore, the main objective of the research was to investigate the correlation between the items of attitude and motivation in spoken En

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Renwick, Margaret E., and Caitlin N. Cassidy. "Detecting palatalization in spontaneous spoken English." Journal of the Acoustical Society of America 137, no. 4 (2015): 2267. http://dx.doi.org/10.1121/1.4920277.

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Brownlees, Nicholas. "Spoken Discourse in Early English Newspapers." Media History 11, no. 1-2 (2005): 69–85. http://dx.doi.org/10.1080/1368880052000342424.

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Nesselhauf, Nadja, and Ute Römer. "Lexical-grammatical patterns in spoken English." International Journal of Corpus Linguistics 12, no. 3 (2007): 297–333. http://dx.doi.org/10.1075/ijcl.12.3.02nes.

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Based on a large set of data from one of the biggest available corpora of spoken British English (the 10-million word spoken component of the BNC), this article explores central lexical-grammatical aspects of progressive forms with future time reference. Among the phenomena investigated are verb preferences, adverbial co-selection, subject types, and negation. It is demonstrated that future time progressives in spoken British English are patterned to a considerable extent (for example that it is individual verbs, rather than semantic groups of verbs, that preferably occur in such constructions

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Laws, Jacqueline, and Chris Ryder. "Register variation in spoken British English." International Journal of Corpus Linguistics 23, no. 1 (2018): 1–27. http://dx.doi.org/10.1075/ijcl.16036.law.

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Abstract The aim of this paper is to identify the effect of register variation in spoken British English on the occurrence of the four principal verb-forming suffixes: ‑ate, ‑en, ‑ify and ‑ize, by building on the work of Biber et al. (1999), Plag et al. (1999) and Schmid (2011). Register variation effects were compared between the less formal Demographically-Sampled and the more formal Context-Governed components of the original 1994 version of the British National Corpus. The pattern of ‑ize derivatives revealed the most marked register-based differences with respect to frequency counts and t

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Alexander, James D. "The stress factor in spoken English." English Today 2, no. 1 (1986): 31–34. http://dx.doi.org/10.1017/s026607840000170x.

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Like Russian and Arabic but unlike French and Japanese, spoken English is a flow of stronger and weaker syllables. Usually the stronger syllables are ‘obvious’, but sometimes they are not – and foreign learners always have problems. The stress patterns of English are complex – they shift with the passing of the years and are by no means the same everywhere.

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Dressler, Wolfgang U., and Katarzyna Dziubalska-Kolaczyk. "Sound Patterns of Spoken English (review)." Language 81, no. 1 (2005): 274–76. http://dx.doi.org/10.1353/lan.2005.0014.

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Gráf, Tomáš. "Verb Errors in Advanced Spoken English." AUC PHILOLOGICA 2017, no. 1 (2017): 131–49. http://dx.doi.org/10.14712/24646830.2017.8.

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Powell, Robert G. "Measuring minimal proficiency in spoken English." Communication Reports 3, no. 1 (1990): 37–44. http://dx.doi.org/10.1080/08934219009367499.

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47

Park, Myungkwan. "On gapless relatives in spoken English." Language and Linguistics 103 (February 28, 2024): 29–52. http://dx.doi.org/10.20865/202410302.

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48

Wang, Shuli, and Xiuchuan Shi. "Research on Correction Method of Spoken Pronunciation Accuracy of AI Virtual English Reading." Advances in Multimedia 2021 (December 17, 2021): 1–12. http://dx.doi.org/10.1155/2021/6783205.

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In order to improve the pronunciation accuracy of spoken English reading, this paper combines artificial intelligence technology to construct a correction model of the spoken pronunciation accuracy of AI virtual English reading. Moreover, this paper analyzes the process of speech synthesis with intelligent speech technology, proposes a statistical parametric speech based on hidden Markov chains, and improves the system algorithm to make it an intelligent algorithm that meets the requirements of the correction system of spoken pronunciation accuracy of AI virtual English reading. Finally, this

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49

Love, Robbie, Claire Dembry, Andrew Hardie, Vaclav Brezina, and Tony McEnery. "The Spoken BNC2014." International Journal of Corpus Linguistics 22, no. 3 (2017): 319–44. http://dx.doi.org/10.1075/ijcl.22.3.02lov.

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Abstract This paper introduces the Spoken British National Corpus 2014, an 11.5-million-word corpus of orthographically transcribed conversations among L1 speakers of British English from across the UK, recorded in the years 2012–2016. After showing that a survey of the recent history of corpora of spoken British English justifies the compilation of this new corpus, we describe the main stages of the Spoken BNC2014’s creation: design, data and metadata collection, transcription, XML encoding, and annotation. In doing so we aim to (i) encourage users of the corpus to approach the data with sens

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50

Genç-Yöntem, Ece, and Evrim Eveyik-Aydın. "The compilation of a developmental spoken English corpus of Turkish EFL learners." Research in Corpus Linguistics 10, no. 1 (2021): 45–62. http://dx.doi.org/10.32714/ricl.10.01.03.

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Although compiling a spoken learner corpus is not a recent enterprise, the number of developmental learner spoken corpora in the field of corpus linguistics is not satisfactory. This report describes the compilation of the Yeditepe Spoken Corpus of Learner English (YESCOLE), a 119,787-word corpus of Turkish students’ spoken English at tertiary level. YESCOLE was compiled to generate a developmental corpus of spoken interlanguage by collecting samples from learners of different English proficiency levels at regular short intervals over seven months. In order to shed light on the laborious metho

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