Papers by Seunghee Han

2 papers
Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing (2024.findings-emnlp)

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Challenge: Visual speech processing requires context modeling due to the ambiguous nature of lip movements.
Approach: They propose a framework to maximize the context modeling capability by bringing the power of LLMs.
Outcome: The proposed framework maximizes the power of visual speech processing by bringing it to the forefront of the field.
Constructing Korean Learners’ L2 Speech Corpus of Seven Languages for Automatic Pronunciation Assessment (2024.lrec-main)

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Challenge: Multilingual L2 speech corpora for automatic speech assessment are currently available, but lack comprehensive annotations of L2 from non-native speakers of various languages.
Approach: They propose to use Korean learners’ L2 speech corpus of seven languages to develop automatic speech assessment.
Outcome: The proposed corpus contains 1,200 hours of L2 speech data from Korean learners (400 hours for English, 200 hours each for Japanese and Chinese, 100 hours each in French, German, Spanish, and Russian).

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