3 citations · 5 across the 7 of their papers we have counts for
7 papers
Color-based Emotion Representation for Speech Emotion Recognition
Ryotaro Nagase, Ryoichi Takashima, Yoichi Yamashita
Speech emotion recognition (SER) has traditionally relied on categorical or dimensional labels. However, this technique is limited in representing both the diversity and interpreta…
Zero-shot Sound Event Classification Using a Sound Attribute Vector with Global and Local Feature Learning
Yi-Han Lin, Xunquan Chen, Ryoichi Takashima +1
This paper introduces a zero-shot sound event classification (ZS-SEC) method to identify sound events that have never occurred in training data. In our previous work, we proposed a…
Learn to See Faster: Pushing the Limits of High-Speed Camera with Deep Underexposed Image Denoising
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
The ability to record high-fidelity videos at high acquisition rates is central to the study of fast moving phenomena. The difficulty of imaging fast moving scenes lies in a trade-…
Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to p…
Current Source Localization Using Deep Prior with Depth Weighting
Rio Yamana, Hajime Yano, Ryoichi Takashima +2
This paper proposes a novel neuronal current source localization method based on Deep Prior that represents a more complicated prior distribution of current source using convolutio…
FasterRCNN Monitoring of Road Damages: Competition and Deployment
Hascoet Tristan, Yihao Zhang, Persch Andreas +3
Maintaining aging infrastructure is a challenge currently faced by local and national administrators all around the world. An important prerequisite for efficient infrastructure ma…
Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition
Naoyuki Kanda, Shota Horiguchi, Ryoichi Takashima +3
In this paper, we propose a novel auxiliary loss function for target-speaker automatic speech recognition (ASR). Our method automatically extracts and transcribes target speaker's…