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Learning Pronunciation with Google Translate: Focus on English Past -ed


Learning Pronunciation with Google Translate: Focus on English Past -ed

Khademi, Hamidreza (2021) Learning Pronunciation with Google Translate: Focus on English Past -ed. Masters thesis, Concordia University.

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The limited amount of time is one of the most common problems that teachers and second language (L2) students face in language classrooms, particularly for pronunciation instruction. To address the problem, teachers often ask students to engage in self-directed and out-of-classroom activities (e.g., homework) by using technologies such as Text-to-Speech Synthesis (TTS) and Automatic-Speech-Recognition (ASR). However, little is known about the feasibility of using TTS and ASR combined (as found in Google Translate - GT) as pedagogical tools, nor do we understand what happens when the learner is asked to use the technology to learn on their own, outside of their classrooms.
Following a pre-test-post-test design, this mixed-methods one-shot study investigates the pedagogical affordances of GT’s TTS and ASR speech capabilities and how their use can help learners acquire L2 pronunciation. More specifically, the present study focuses on the acquisition of English past -ed pronunciation, a challenging learning target (in terms of phonological awareness, listening discrimination or perception, and production) in a teacher-guided semi-autonomous out-of-class context. Emulating the completion of a homework assignment, 20 Farsi-speaking English learners used GT’s TTS and ASR functions to learn the pronunciation of past -ed allomorphy (/d/, /t/, /id/) through various listening (via TTS) and speaking activities (via ASR).
Findings indicate that there were significant improvements in both the participants’ awareness and perception of the English past -ed allomorphy, thus confirming that GT and its speech capabilities can help learners acquire the target pronunciation feature in these two initial stages of L2 pronunciation development. However, in production (the subsequent stage), only one of the allomorphs (/id/) had improved by the end of the experiment.

Divisions:Concordia University > Faculty of Arts and Science > Education
Item Type:Thesis (Masters)
Authors:Khademi, Hamidreza
Institution:Concordia University
Degree Name:M.A.
Program:Applied Linguistics
Date:8 August 2021
Thesis Supervisor(s):Walcir, Cardoso
Keywords:Text-to-Speech Synthesis (TTS), Automatic-Speech-Recognition (ASR), Google Translate, L2 pronunciation, Awareness, Perception, Production
ID Code:988658
Deposited By: Hamidreza Khademi
Deposited On:29 Nov 2021 16:57
Last Modified:29 Nov 2021 16:57


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