Papers with Quebec English

2 papers
Understanding Computational Models of Semantic Change: New Insights from the Speech Community (2023.emnlp-main)

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Challenge: Using type-level and token-level word embeddings, we obtain semantic change estimates from type-based models and empirical linguistic properties.
Approach: They analyze 40 target words with type-level and token-level word embeddings, empirical linguistic properties, and speaker-provided acceptability ratings and qualitative remarks.
Outcome: The proposed models are able to describe the sociolinguistic issue of contact-induced semantic shifts in Quebec English and are validated by qualitative interviews with 15 speakers from Montreal.
Detecting Contact-Induced Semantic Shifts: What Can Embedding-Based Methods Do in Practice? (2021.emnlp-main)

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Challenge: Existing work on semantic change detection methods has focused on generic research questions and datasets, using them as a training ground for proof-of-concept studies.
Approach: They propose to use type-level embeddings to detect new semantic shifts and token-level embeddeds to isolate regionally specific occurrences.
Outcome: The proposed method is comparable to state-of-the-art on diachrony tasks, but it does not translate to practical value in detecting new semantic shifts.

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