Papers by Trang Tran

2 papers
Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information (N18-1)

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Challenge: acoustic signals provide cues that help listeners disambiguate difficult parses . speech carries useful extra information associated with prosodic structure .
Approach: They propose a model that integrates transcribed text and acoustic-prosodic features into a neural network that accepts text and prosodic feature.
Outcome: The proposed model improves parse and disfluency detection scores over a strong text-only baseline.
Box Embeddings: An open-source library for representation learning using geometric structures (2021.emnlp-demo)

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Challenge: Recent studies have explored alternative vector representations with different inductive biases or capabilities.
Approach: They propose a Python library that extends probabilistic box embeddings to geometric shapes and regions.
Outcome: The proposed library is fully open source and compatible with PyTorch and TensorFlow.

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