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1
Primates evolved spectrally complex calls in compensation for reduction in olfactory cognition ...
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How, when and why early gesture use predicts language development ...
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3
Preschoolers' Learning of Words with Emotional Variability in Shared Book Reading ...
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4
A Grounded Approach to Modeling Generic Knowledge Acquisition ...
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5
Frequency vs. Salience in First Language Acquisition: The Acquisition of Aspect Marking in Chintang ...
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6
Now or Later: Representational Convergence in Simulated Simultaneous and Sequential Bilingual Learning Contexts ...
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7
Bilinguals Infer in L2 Similarly, but not in Dual-language ...
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8
Extent of bilingual experience in modulating young adults’ processing of social-communicative cues in a cue integration task: An eye-tracking study ...
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9
Using Machine Learning to Predict Bilingual Language Proficiency from Reaction Time Priming Data ...
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10
Bilinguals Infer in L2 Similarly, but not in Dual-language ...
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11
Cognitive Argumentation and the Selection Task ...
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12
From Alien Zoo to Spy School: A Preregistered Study of Linguistic Sound Symbolism and its Links to Reading in 8-year-olds ...
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13
AgeNet: A Neurobiological Model of Age-related Word Retrieval Deficits ...
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14
Phonological Interactions, Process Types, and Minimum Description Length Principles ...
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15
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
Abstract: The primary goals of computer-assisted pronunciation training (CAPT) systems are to provide a personalized interactive environment and to accurately diagnose mispronunciations. Automatic speech recognition (ASR) systems have been shown to be an effective tool for diagnosing mispronunciations. While the data ASR systems output can be difficult for the layperson to understand, presenting it in a multimodal fashion can make it easier and feeding it into an automated narrative system can produce personalized feedback. In the absence of native speech examples, synthetic examples produced by text-to-speech (TTS) engines have proven to be an adequate substitute, making data collection easier and allowing for larger CAPT systems. In this work we present the SpeakEasy pronunciation trainer, a CAPT system that leverages ASR, TTS, automated narrative systems, and multimodal data representation to provide a personalized interactive environment that tracks a user's progress over time. ...
Keyword: Cognitive Linguistics; Cognitive Science; Computational Intelligence; Computational Linguistics; E-Learning; Phonetics; Phonology; Semantics
URL: https://dx.doi.org/10.48448/aa25-n461
https://underline.io/lecture/26896-speakeasy-pronunciation-trainer-personalized-multimodal-pronunciation-training
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16
Simulating the factors that correct the erroneous process of phonological generation in Japanese ...
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17
Exploring the Structure and Grounding of Concrete and Abstract Categories ...
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18
Episodic Memory Cues in Acquisition of Novel Visual-Phonological Associations: a Webcam-Based Eye-Tracking Study ...
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19
The online advantage of repairing metrical structure: Stress shift in pupillometry ...
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20
Of Pieces and Patterns: Modeling Poetic Devices ...
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