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Cox, Troy L.; Brown, Alan V.; Thompson, Gregory L. – Language Testing, 2023
The rating of proficiency tests that use the Inter-agency Roundtable (ILR) and American Council on the Teaching of Foreign Languages (ACTFL) guidelines claims that each major level is based on hierarchal linguistic functions that require mastery of multidimensional traits in such a way that each level subsumes the levels beneath it. These…
Descriptors: Oral Language, Language Fluency, Scoring, Cues
Miyamoto, Mayu – ProQuest LLC, 2019
Despite an emphasis on oral communication in most foreign language classrooms, the resource-intensive nature (i.e. time and manpower) of speaking tests hinder regular oral assessments. A possible solution is the development of a (semi-) automated scoring system. When it is used in conjunction with human raters, the consistency of computers can…
Descriptors: Second Language Learning, Speech Communication, Oral Language, Foreign Countries
Chen, Lei; Zechner, Klaus; Yoon, Su-Youn; Evanini, Keelan; Wang, Xinhao; Loukina, Anatassia; Tap, Jidong; Davis, Lawrence; Lee, Chong Min; Ma, Min; Mundowsky, Robert; Lu, Chi; Leong, Chee Wee; Gyawali, Binod – ETS Research Report Series, 2018
This research report provides an overview of the R&D efforts at Educational Testing Service related to its capability for automated scoring of nonnative spontaneous speech with the "SpeechRater"? automated scoring service since its initial version was deployed in 2006. While most aspects of this R&D work have been published in…
Descriptors: Computer Assisted Testing, Scoring, Test Scoring Machines, Speech Tests
Hannah, L.; Kim, H.; Jang, E. E. – Language Assessment Quarterly, 2022
As a branch of artificial intelligence, automated speech recognition (ASR) technology is increasingly used to detect speech, process it to text, and derive the meaning of natural language for various learning and assessment purposes. ASR inaccuracy may pose serious threats to valid score interpretations and fair score use for all when it is…
Descriptors: Task Analysis, Artificial Intelligence, Speech Communication, Audio Equipment
Kobayashi, Yuichiro; Abe, Mariko – Journal of Pan-Pacific Association of Applied Linguistics, 2016
The purpose of the present study is to assess second language (L2) spoken English using automated scoring techniques. Automated scoring aims to classify a large set of learners' oral performance data into a small number of discrete oral proficiency levels. In automated scoring, objectively measurable features such as the frequencies of lexical and…
Descriptors: Second Language Learning, Computer Assisted Testing, Scoring, Automation
Gleason, Jesse – Hispania, 2014
Communicative approaches to language teaching that emphasize the importance of speaking (e.g., task-based language teaching) require innovative and evidence-based means of assessing oral language. Nonetheless, research has yet to produce an adequate assessment model for oral language (Chun 2006; Downey et al. 2008). Limited by automatic speech…
Descriptors: Scoring, Linguistics, Oral Language, Language Tests
Ling, Guangming; Mollaun, Pamela; Xi, Xiaoming – Language Testing, 2014
The scoring of constructed responses may introduce construct-irrelevant factors to a test score and affect its validity and fairness. Fatigue is one of the factors that could negatively affect human performance in general, yet little is known about its effects on a human rater's scoring quality on constructed responses. In this study, we compared…
Descriptors: Evaluators, Fatigue (Biology), Scoring, Performance
Ashwell, Tim; Elam, Jesse R. – JALT CALL Journal, 2017
The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Language Tests
Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David – Language Testing, 2012
This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…
Descriptors: Scoring, Classification, Weighted Scores, Comparative Analysis
Thompson, Carrie A. – ProQuest LLC, 2013
The Missionary Training Center (MTC), affiliated with the Church of Jesus Christ of Latter-day Saints, needs a reliable and cost effective way to measure the oral language proficiency of missionaries learning Spanish. The MTC needed to measure incoming missionaries' Spanish language proficiency for training and classroom assignment as well as to…
Descriptors: Religious Cultural Groups, Second Language Learning, Second Language Instruction, Interviews
Bridgeman, Brent; Powers, Donald; Stone, Elizabeth; Mollaun, Pamela – Language Testing, 2012
Scores assigned by trained raters and by an automated scoring system (SpeechRater[TM]) on the speaking section of the TOEFL iBT[TM] were validated against a communicative competence criterion. Specifically, a sample of 555 undergraduate students listened to speech samples from 184 examinees who took the Test of English as a Foreign Language…
Descriptors: Undergraduate Students, Speech Communication, Rating Scales, Scoring
Davis, Lawrence Edward – ProQuest LLC, 2012
Speaking performance tests typically employ raters to produce scores; accordingly, variability in raters' scoring decisions has important consequences for test reliability and validity. One such source of variability is the rater's level of expertise in scoring. Therefore, it is important to understand how raters' performance is influenced by…
Descriptors: Evaluators, Expertise, Scores, Second Language Learning
Van Moere, Alistair; Suzuki, Masanori; Downey, Ryan; Cheng, Jian – Australian Review of Applied Linguistics, 2009
This paper discusses the development of an assessment to satisfy the International Civil Aviation Organization (ICAO) Language Proficiency Requirements. The Versant Aviation English Test utilizes speech recognition technology and a computerized testing platform, such that test administration and scoring are fully automated. Developed in…
Descriptors: Scoring, Test Construction, Language Proficiency, Standards
Zechner, Klaus; Bejar, Isaac I.; Hemat, Ramin – ETS Research Report Series, 2007
The increasing availability and performance of computer-based testing has prompted more research on the automatic assessment of language and speaking proficiency. In this investigation, we evaluated the feasibility of using an off-the-shelf speech-recognition system for scoring speaking prompts from the LanguEdge field test of 2002. We first…
Descriptors: Role, Computer Assisted Testing, Language Proficiency, Oral Language
Xi, Xiaoming; Mollaun, Pam – ETS Research Report Series, 2006
This study explores the utility of analytic scoring for the TOEFL® Academic Speaking Test (TAST) in providing useful and reliable diagnostic information in three aspects of candidates' performance: delivery, language use, and topic development. G studies were used to investigate the dependability of the analytic scores, the distinctness of the…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Oral Language
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