Papers with adversarial discriminators

2 papers
Emotion Detection with Neural Personal Discrimination (D19-1)

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Challenge: Existing approaches to automatically predict the emotions of posts consider each post individually and predict their emotions independently.
Approach: They propose a Neural Personal Discrimination approach to identify personal attributes from posts and connect relevant posts with similar attributes to jointly learn their emotions.
Outcome: The proposed approach improves on existing models by capturing attributes-aware words and predicting emotions among relevant posts.
ESC: Efficient Speech Coding with Cross-Scale Residual Vector Quantized Transformers (2024.emnlp-main)

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Challenge: Existing neural speech codecs trade model complexity for reconstruction performance . ESC is a lightweight, parameter-efficient speech coder .
Approach: They propose an efficient speech codec based on a cross-scale residual vector quantization scheme and transformers that can achieve high-fidelity speech reconstruction with significantly lower model complexity.
Outcome: The proposed codec achieves high-fidelity speech reconstruction with significantly lower model complexity.

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