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Found 10 papers, 4 papers with code
Collection and Analysis of Dialogues Provided by Two Speakers Acting as One
We are studying a cooperation style where multiple speakers can provide both advanced dialogue services and operator education.
Using joint training speaker encoder with consistency loss to achieve cross-lingual voice conversion and expressive voice conversion
Voice conversion systems have made significant advancements in terms of naturalness and similarity in common voice conversion tasks.
Investigating the impact of free energy based behavior on human in human-agent interaction
Humans communicate non-verbally by sharing physical rhythms, such as nodding and gestures, to involve each other.
CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer
In this study, we explore the transformer's ability to capture intra-relations among frames by augmenting the receptive field of models.
Probabilistic Human-like Gesture Synthesis from Speech using GRU-based WGAN
The motions synthesized by the proposed system are evaluated via an objective measure and a subjective experiment, showing that the proposed model outperforms a baseline model which is trained by a state-of-the-art GAN-based algorithm, using the same dataset.
SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification
Text categorization is the task of assigning labels to documents written in a natural language, and it has numerous real-world applications including sentiment analysis as well as traditional topic assignment tasks.
Introduction method for argumentative dialogue using paired question-answering interchange about personality
The results suggest that inserting the question-answer dialogue enhances familiarity and naturalness.
Show, Attend and Interact: Perceivable Human-Robot Social Interaction through Neural Attention Q-Network
For a safe, natural and effective human-robot social interaction, it is essential to develop a system that allows a robot to demonstrate the perceivable responsive behaviors to complex human behaviors.
Robot gains Social Intelligence through Multimodal Deep Reinforcement Learning
For robots to coexist with humans in a social world like ours, it is crucial that they possess human-like social interaction skills.
