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Improving literacy in developing countries using speech recognition-supported games on mobile devices

Learning to read in a second language is challenging, but highly rewarding. synthesis of research findings suggests that practicing...
Learning to read in a second language is challenging, but highly rewarding. synthesis of research findings suggests that practicing recalling and vocalizing words for expressing an intended meaning could improve word reading skills - including reading in a second...
Learning to read in a second language is challenging, but highly rewarding. synthesis of research findings suggests that practicing recalling and vocalizing words for expressing an intended meaning could improve word reading skills - including reading in a second language - more than silent recognition of what the given words mean. Many language learning software do not support this instructional approach, owing to the technical challenges of incorporating speech recognition support to check that the learner is vocalizing the correct word. In this paper, we present results from a usability test and two subsequent experiments that explore the use of two speech recognition-enabled mobile games to help rural children in India read words with understanding. Through a working speech recognition prototype, we discuss two major contributions of this work: first, we give empirical evidence that shows the extent to which productive training (i.e. vocalizing words) is superior to receptive vocabulary training, and discuss the use of scaffolding hints to ""unpack"" factors in the learner's linguistic knowledge that may impact reading. Second, we discuss what our results suggest for future research in HCI.
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Highly accurate children’s speech recognition for interactive reading tutors using subword units

Speech technology offers great promise in the field of automated literacy and reading tutors for children. In such applications...
Speech technology offers great promise in the field of automated literacy and reading tutors for children. In such applications speech recognition can be used to track the reading position of the child, detect oral reading miscues, assessing comprehension of...
Speech technology offers great promise in the field of automated literacy and reading tutors for children. In such applications speech recognition can be used to track the reading position of the child, detect oral reading miscues, assessing comprehension of the text being read by estimating if the prosodic structure of the speech is appropriate to the discourse structure of the story, or by engaging the child in interactive dialogs to assess and train comprehension. Despite such promises, speech recognition systems exhibit higher error rates for children due to variabilities in vocal tract length, formant frequency, pronunciation, and grammar. In the context of recognizing speech while children are reading out loud, these problems are compounded by speech production behaviors affected by difficulties in recognizing printed words that cause pauses, repeated syllables and other phenomena. To overcome these challenges, we present advances in speech recognition that improve accuracy and modeling capability in the context of an interactive literacy tutor for children. Specifically, this paper focuses on a novel set of speech recognition techniques which can be applied to improve oral reading recognition. The proposed subword unit based speech recognition framework is shown to provide equivalent accuracy to a whole-word based speech recognizer while enabling detection of oral reading events and finer grained speech analysis during recognition. The efficacy of the approach is demonstrated using data collected from children in grades 3–5.
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