66 citations · 140 across the 14 of their papers we have counts for
14 papers
Using joint training speaker encoder with consistency loss to achieve cross-lingual voice conversion and expressive voice conversion
Houjian Guo, Chaoran Liu, Carlos Toshinori Ishi +1
Voice conversion systems have made significant advancements in terms of naturalness and similarity in common voice conversion tasks. However, their performance in more complex task…
Exploring the Adaptive Behaviors of Particle Lenia: A Perturbation-Response Analysis for Computational Agency
Kazuya Horibe, Keisuke Suzuki, Takato Horii +1
A firm cognitive subject or ``individual'' is presupposed for the emergence of mind. However, with the development of recent information technology, the ``individual'' has become m…
QuickVC: Any-to-many Voice Conversion Using Inverse Short-time Fourier Transform for Faster Conversion
Houjian Guo, Chaoran Liu, Carlos Toshinori Ishi +1
With the development of automatic speech recognition (ASR) and text-to-speech (TTS) technology, high-quality voice conversion (VC) can be achieved by extracting source content info…
Influence of collaborative customer service by service robots and clerks in bakery stores
Yuki Okafuji, Sichao Song, Jun Baba +2
In recent years, various service robots have been introduced in stores as recommendation systems. Previous studies attempted to increase the influence of these robots by improving…
Service Robots in a Bakery Shop: A Field Study
Sichao Song, Baba Jun, Junya Nakanishi +2
In this paper, we report on a field study in which we employed two service robots in a bakery store as a sales promotion. Previous studies have explored public applications of serv…
Investigating the impact of free energy based behavior on human in human-agent interaction
Kazuya Horibe, Yuanxiang Fan, Yutaka Nakamura +1
Humans communicate non-verbally by sharing physical rhythms, such as nodding and gestures, to involve each other. This sharing of physicality creates a sense of unity and makes hum…
CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer
Changzeng Fu, Chaoran Liu, Carlos Toshinori Ishi +1
In this study, we explore the transformer's ability to capture intra-relations among frames by augmenting the receptive field of models. Concretely, we propose a CycleGAN-based mod…
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…
Show, Attend and Interact: Perceivable Human-Robot Social Interaction through Neural Attention Q-Network
Ahmed Hussain Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa +1
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 com…
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…