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This meta-analytic study explores the overall effectiveness of automatic speech recognition (ASR) on ESL/EFL student pronunciation performance. Data with 15 studies representing 38 effect sizes found from 2008 to 2021 were meta-analyzed. The findings of the meta-analysis indicated that ASR has a medium overall effect size (g = 0.69). Results from moderator analyses suggest that (1) ASR with explicit corrective feedback is largely effective, while ASR with indirect feedback (e.g. ASR dictation) is moderately effective; (2) ASR has a large effect on segmental pronunciation but a small effect on suprasegmental pronunciation; (3) medium to long treatment duration of ASR results in higher learning outcomes, but short duration offers no differential effect compared to a non-ASR condition; (4) practicing pronunciation with peers in an ASR condition produces a large effect, but the effect is small when practicing alone; (5) ASR is largely effective for adult (i.e. 18 years old and above) and intermediate English learners. Overall, ASR is a beneficial application and is recommended for assisting L2 student pronunciation development.
A model of Martin-Löf extensional type theory with universes is formalized in Agda, an interactive proof system based on Martin-Löf intensional type theory. This may be understood, we claim, as a solution to the old problem of modeling the full extensional theory in the intensional theory. Types are interpreted as setoids, and the model is therefore a setoid model.We solve the problem of interpreting type universes by utilizing Aczel’s type of iterative sets and show how it can be made into a setoid of small setoids containing the necessary setoid constructions. In addition, we interpret the bracket types of Awodey and Bauer. Further quotient types should be interpretable.