6,724 research outputs found

    Using State-of-the-Art Speech Models to Evaluate Oral Reading Fluency in Ghana

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    This paper reports on a set of three recent experiments utilizing large-scale speech models to evaluate the oral reading fluency (ORF) of students in Ghana. While ORF is a well-established measure of foundational literacy, assessing it typically requires one-on-one sessions between a student and a trained evaluator, a process that is time-consuming and costly. Automating the evaluation of ORF could support better literacy instruction, particularly in education contexts where formative assessment is uncommon due to large class sizes and limited resources. To our knowledge, this research is among the first to examine the use of the most recent versions of large-scale speech models (Whisper V2 wav2vec2.0) for ORF assessment in the Global South. We find that Whisper V2 produces transcriptions of Ghanaian students reading aloud with a Word Error Rate of 13.5. This is close to the model's average WER on adult speech (12.8) and would have been considered state-of-the-art for children's speech transcription only a few years ago. We also find that when these transcriptions are used to produce fully automated ORF scores, they closely align with scores generated by expert human graders, with a correlation coefficient of 0.96. Importantly, these results were achieved on a representative dataset (i.e., students with regional accents, recordings taken in actual classrooms), using a free and publicly available speech model out of the box (i.e., no fine-tuning). This suggests that using large-scale speech models to assess ORF may be feasible to implement and scale in lower-resource, linguistically diverse educational contexts

    New Perspectives in Teaching Pronunciation

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    pp.165-18

    Technology-based reading intervention programs for elementary grades: An analytical review

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    In modern societies, the role of reading is becoming increasingly crucial. Hence, any impairment to the reading ability can seriously limit a person's aspirations. The enormous importance of reading as an essential skill in modern life has encouraged many researchers to try and find more effective intervention approaches. Technology has been used extensively to assist and enhance literacy learning. This analytical review aims at presenting a comprehensive overview of the existing research on technology-based or technology-assisted reading interventions for elementary grades, between 2000 and 2017, along with analyzing various aspects of these studies. After extensive research, 42 articles have met the inclusion criteria, which have evaluated a total of 32 reading programs. The studies are classified into six categories of phonological awareness, phonics, vocabulary, comprehension, fluency, and multi-component. Each reading category begins with a brief introduction. Then, the content and instructional mechanisms of each program in the category is explained, alongside the outcome of its interventions. It is found that vocabulary interventions, as well as using mobile, tablet and other non-computer technologies are massively overlooked. Furthermore, a very limited number of programs focused on fluency, none of them addressed all its components. In addition, despite the required long-term practice for fostering fluency, the reviewed studies have an average intervention time shorter than other intervention categories. This paper provides researchers and solution developers with an extensive and informative review of the current state of the art in reading interventions. Additionally, it identifies the current knowledge gaps and defines future research directions to develop effective reading programs

    Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics

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    Automatic assessment of reading fluency using automatic speech recognition (ASR) holds great potential for early detection of reading difficulties and subsequent timely intervention. Precise assessment tools are required, especially for languages other than English. In this study, we evaluate six state-of-the-art ASR-based systems for automatically assessing Dutch oral reading accuracy using Kaldi and Whisper. Results show our most successful system reached substantial agreement with human evaluations (MCC = .63). The same system reached the highest correlation between forced decoding confidence scores and word correctness (r = .45). This system's language model (LM) consisted of manual orthographic transcriptions and reading prompts of the test data, which shows that including reading errors in the LM improves assessment performance. We discuss the implications for developing automatic assessment systems and identify possible avenues of future research

    An Analysis of Dyslexia Legisation and Implementation Guidelines in Midwestern States

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    The purpose of this thesis is to describe dyslexia legislation and implementation guidelines in South Dakota and selected surrounding states. Dyslexia has been defined as a language-learning disability that affects a person\u27s reading and writing skills negatively. Federal legislation, The Individuals with Disabilities in Legislation Act (2004), identifies dyslexia as a specific learning disability; however, distinguish dyslexia from a broader category. Legislation and requirements are being recently passed in multiple states, affecting dyslexia policy. This thesis will provide an overview of the legislation and guidelines of dyslexia in Midwest region. Best practices in assessment and instruction for dyslexia have been reviewed, identified, and used as the standard for the evaluation within this paper. This research is important because it can inform legislators about dyslexic specific legislation, particularly in South Dakota. This document will help parents, speech-language pathologists, and other professionals understand better what the eligibility laws for dyslexia explicitly state. Researching Midwest states\u27 law and policy on dyslexia will provide a comparison of legislation in similar states providing a framework in establishing legislation that would best serve the needs of students in the K-12 schools, particularly students with dyslexia and specifically in the state of South Dakota

    Utilising voice recognition software to improve reading fluency of struggling adolescent readers

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    Approximately 15-20% of secondary students in Australia experience reading difficulties. For many, the cognitive effort required to decode words or the lack of automaticity in the elements that contribute to fluent reading prevents effective reading comprehension. Because reading comprehension is of critical importance across the curriculum, students with difficulties in this area are at significant academic risk. One effective method of improving reading fluency is ‘repeated readings’ (NICHHD, 2000). The purpose of this study was to examine whether the use of repeated readings delivered via a home-based program employing voice recognition software (VRS) could improve the reading fluency and self-perception as readers of adolescent students experiencing reading difficulties. The intervention was designed to overcome the problems associated with delivering a repeated reading program within a secondary English classroom. These problems relate to the amount of time required to conduct such a program within the constraints of the existing curriculum, and the reluctance of students to participate in a program that would draw attention to their reading difficulties. A treatment group participated in a home-based repeated reading program using VRS over a 20-week period and their results were compared to a comparison group who participated in a more traditional school-based repeated reading program. Reading fluency, comprehensions and reader self-perception were measured before and after the intervention. Data were analysed using descriptive statistics and case studies. The intervention reported in this study resulted in improved reading rate, accuracy and comprehension for both the home-based treatment group and a school-based comparison group, with evidence of larger gains in the treatment group. The students’ perceptions of themselves as readers, however, did not show significant gains

    Automatic Pronunciation Assessment -- A Review

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    Pronunciation assessment and its application in computer-aided pronunciation training (CAPT) have seen impressive progress in recent years. With the rapid growth in language processing and deep learning over the past few years, there is a need for an updated review. In this paper, we review methods employed in pronunciation assessment for both phonemic and prosodic. We categorize the main challenges observed in prominent research trends, and highlight existing limitations, and available resources. This is followed by a discussion of the remaining challenges and possible directions for future work.Comment: 9 pages, accepted to EMNLP Finding
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