18 citations · 34 across the 8 of their papers we have counts for
8 papers
From Sign Language Generation to Humanoid Execution: Vision-Language Guided Retargeting with Collision Mitigation
Nabeela Khan, Bowen Wu, Runwu Shi +5
Recent sign language generation (SLG) systems increasingly output dense 3D body representations, which better preserve full-body kinematics and geometry for downstream embodiment o…
What Do Humans Hear When Interacting? Experiments on Selective Listening for Evaluating ASR of Spoken Dialogue Systems
Kiyotada Mori, Seiya Kawano, Chaoran Liu +3
Spoken dialogue systems (SDSs) utilize automatic speech recognition (ASR) at the front end of their pipeline. The role of ASR in SDSs is to recognize information in user speech rel…
Quadrupedal Spine Control Strategies: Exploring Correlations Between System Dynamic Responses and Human Perspectives
Nicholas Hafner, Chaoran Liu, Carlos Ishi +1
Unlike their biological cousins, the majority of existing quadrupedal robots are constructed with rigid chassis. This results in motion that is either beetle-like or distinctly rob…
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…
I Know Your Feelings Before You Do: Predicting Future Affective Reactions in Human-Computer Dialogue
Yuanchao Li, Koji Inoue, Leimin Tian +5
Current Spoken Dialogue Systems (SDSs) often serve as passive listeners that respond only after receiving user speech. To achieve human-like dialogue, we propose a novel future pre…
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…
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…
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…