18 citations · 23 across the 5 of their papers we have counts for
6 papers
Decoupling Speaker-Independent Emotions for Voice Conversion Via Source-Filter Networks
Zhaojie Luo, Shoufeng Lin, Rui Liu +3
Emotional voice conversion (VC) aims to convert a neutral voice to an emotional (e.g. happy) one while retaining the linguistic information and speaker identity. We note that the d…
Fusion with Hierarchical Graphs for Mulitmodal Emotion Recognition
Shuyun Tang, Zhaojie Luo, Guoshun Nan +2
Automatic emotion recognition (AER) based on enriched multimodal inputs, including text, speech, and visual clues, is crucial in the development of emotionally intelligent machines…
Behavioral assessment of a humanoid robot when attracting pedestrians in a mall
Yuki Okafuji, Yasunori Ozaki, Jun Baba +4
Research currently being conducted on the use of robots as human labor support technology. In particular, the service industry needs to allocate more manpower, and it will be impor…
SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification
Changzeng Fu, Chaoran Liu, Carlos Toshinori Ishi +2
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…
Intrinsically motivated reinforcement learning for human-robot interaction in the real-world
Ahmed Hussain Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa +1
For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limite…
Robot gains Social Intelligence through Multimodal Deep Reinforcement Learning
Ahmed Hussain Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa +1
For robots to coexist with humans in a social world like ours, it is crucial that they possess human-like social interaction skills. Programming a robot to possess such skills is a…