Papers with correlation score

3 papers
Methods of Automatic Matrix Language Determination for Code-Switched Speech (2024.emnlp-main)

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Challenge: Code-switching (CS) is the process of speakers switching between two or more languages in spoken or written language.
Approach: They propose to use the Matrix Language Frame theory to describe CS speech . they compare MLID of English/Mandarin and English/Spanish CS to acoustic language identity .
Outcome: The proposed models outperform monolingual models in acoustic language identity recognition tasks.
Pcc-tuning: Breaking the Contrastive Learning Ceiling in Semantic Textual Similarity (2024.emnlp-main)

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Challenge: Semantic Textual Similarity (STS) is a key indicator of the encoding capabilities of embedding models.
Approach: They propose to use Pearson’s correlation coefficient as a loss function to refine model performance beyond contrastive learning to achieve a Spearman’s ceiling.
Outcome: The proposed method surpasses state-of-the-art strategies with minimal amount of fine-grained annotated samples.
LASER: An LLM-based ASR Scoring and Evaluation Rubric (2025.emnlp-main)

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Challenge: Standard ASR evaluation metrics like word error rate penalize morphological and syntactic nuances that do not significantly alter sentence semantics.
Approach: They propose an LLM-based scoring rubric LASER that leverages state-of-the-art LLMs’ in-context learning abilities to learn from prompts with detailed examples.
Outcome: The proposed scoring rubric combines state-of-the-art learning capabilities with a high correlation score with human annotations.

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