Search Results for author:
Found 6 papers, 1 papers with code
Frame-level emotional state alignment method for speech emotion recognition
To address this problem, we propose a frame-level emotional state alignment method for SER.
CONCSS: Contrastive-based Context Comprehension for Dialogue-appropriate Prosody in Conversational Speech Synthesis
In this paper, we introduce a contrastive learning-based CSS framework, CONCSS.
Learning to Predict Persona Information forDialogue Personalization without Explicit Persona Description
Personalizing dialogue agents is important for dialogue systems to generate more specific, consistent, and engaging responses.
Learning from Perturbations: Diverse and Informative Dialogue Generation with Inverse Adversarial Training
By giving higher rewards for responses whose output probability reduces more significantly when dialogue history is perturbed, the model is encouraged to generate more diverse and consistent responses.
DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation
The core of our method includes a bias representation module, a bias-aware user modeling module, and a bias-aware click prediction module.
Connecting the Dots Between Fact Verification and Fake News Detection
Fact verification models have enjoyed a fast advancement in the last two years with the development of pre-trained language models like BERT and the release of large scale datasets such as FEVER.
