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JALT CALL Journal, v13 n1 p59-76 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 had to assess its accuracy with our Japanese EFL learners; and, on the basis of these trials, we needed to evaluate the potential for using the API for our purposes. Through comparing our own assessments of the learners' pronunciation with the system's ability to transcribe utterances, we were able to ascertain that the learners' pronunciation of certain sounds is probably the single biggest reason for a fall in recognition accuracy compared to native speaker input. However, we argue that pronunciation may not be an insurmountable barrier to using this speech recognition system for our EFL purposes. By going through this double screening process, we feel we have arrived at a set of items which can be used to assess student's grammatical ability in an EI test using a custom Google Web Speech system.

Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Language Tests, Native Speakers, Linguistic Input, Pronunciation, Oral Language, Scoring, Computer Software, Test Items, Barriers, Audio Equipment, Speech Communication, Japanese, Native Language, Teaching Methods, Comparative Analysis, Computer Assisted Instruction, Test Preparation, Foreign Countries, College Students, Computer Assisted Testing, Accuracy, Statistical Analysis, Scores

JALT CALL SIG. 1-6-1 Nishiwaseda Shinjuku-ku, Tokyo, 169-8050, Japan. e-mail: journal!; Web site:

Autor: Ashwell, Tim; Elam, Jesse R.


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