Papers with cross-language scenario

2 papers
Coherent or Not? Stressing a Neural Language Model for Discourse Coherence in Multiple Languages (2023.findings-acl)

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Challenge: Existing work on coherence assessment using NLMs focuses on properties acquired from stand-alone sentences, but their ability to model discourse and pragmatic phenomena is still unclear.
Approach: They propose to use a Neural Language Model to assess coherence in multiple languages to compare models' performance and to examine their performance in a cross-language scenario.
Outcome: The proposed model can model coherent and incoherent text in multiple languages and in-domain settings.
AudioVSR: Enhancing Video Speech Recognition with Audio Data (2024.emnlp-main)

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Challenge: Recent work has shown poor performance with non-Indo-European languages . previous work primarily utilizes video information to build VSR models .
Approach: They propose a generative model for data inflation that integrates synthetic data with authentic visual data to enhance the VSR model.
Outcome: The proposed model improves on the audio-visual alignment problem in audio-video tasks.

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