788 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NTT (Japan)JP13 papers
- Nagoya UniversityJP3 papers
- Johns Hopkins UniversityUS2 papers
- Kyoto UniversityJP2 papers
- Mitsubishi Electric Research Laboratories (United States)US2 papers
- Mitsubishi Electric (United States)US2 papers
- Preferred Networks (Japan)JP2 papers
- RIKEN Center for Advanced Intelligence ProjectJP2 papers
- Waseda UniversityJP2 papers
- Aalto UniversityFI1 paper
- Academia SinicaTW1 paper
- Brocade (United States)US1 paper
13 papers
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech
Xin Wang, Junichi Yamagishi, Massimiliano Todisco +37
Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is v…
A Comparative Study on Transformer vs RNN in Speech Applications
Shigeki Karita, Nanxin Chen, Tomoki Hayashi +10
Sequence-to-sequence models have been widely used in end-to-end speech processing, for example, automatic speech recognition (ASR), speech translation (ST), and text-to-speech (TTS…
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara +2
We propose Absum, which is a regularization method for improving adversarial robustness of convolutional neural networks (CNNs). Although CNNs can accurately recognize images, rece…
Variational Autoencoder with Implicit Optimal Priors
Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka +2
The variational autoencoder (VAE) is a powerful generative model that can estimate the probability of a data point by using latent variables. In the VAE, the posterior of the laten…
Interpretable Adversarial Perturbation in Input Embedding Space for Text
Motoki Sato, Jun Suzuki, Hiroyuki Shindo +1
Following great success in the image processing field, the idea of adversarial training has been applied to tasks in the natural language processing (NLP) field. One promising appr…
On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness
Shinsaku Sakaue
Maximization of {\it non-submodular} functions appears in various scenarios, and many previous works studied it based on some measures that quantify the closeness to being submodul…
ESPnet: End-to-End Speech Processing Toolkit
Shinji Watanabe, Takaaki Hori, Shigeki Karita +9
This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts w…
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch, Mathieu Blondel
Dynamic programming (DP) solves a variety of structured combinatorial problems by iteratively breaking them down into smaller subproblems. In spite of their versatility, DP algorit…
Secure Quantum Network Coding on Butterfly Network
Masaki Owari, Go Kato, Masahito Hayashi
Quantum network coding on the butterfly network has been studied as a typical example of quantum multiple cast network. We propose secure quantum network coding on the butterfly ne…
A Fast Exact Quantum Algorithm for Solitude Verification
Seiichiro Tani
Solitude verification is arguably one of the simplest fundamental problems in distributed computing, where the goal is to verify that there is a unique contender in a network. This…
Knowledge-Defined Networking
Albert Mestres, Alberto Rodriguez-Natal, Josep Carner +17
The research community has considered in the past the application of Artificial Intelligence (AI) techniques to control and operate networks. A notable example is the Knowledge Pla…
Localized Lasso for High-Dimensional Regression
Makoto Yamada, Koh Takeuchi, Tomoharu Iwata +2
We introduce the localized Lasso, which is suited for learning models that are both interpretable and have a high predictive power in problems with high dimensionality and smal…
Perturbation theory in Lagrangian hydrodynamics for a cosmological fluid with velocity dispersion
Takayuki Tatekawa, Momoko Suda, Kei-ichi Maeda +2
We extensively develop a perturbation theory for nonlinear cosmological dynamics, based on the Lagrangian description of hydrodynamics. We solve hydrodynamic equations for a self-g…