457 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of CambridgeGB45 papers
- University of NottinghamGB23 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ21 papers
- Hitachi (Japan)JP13 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR8 papers
- Laboratoire d'Électronique des Technologies de l'InformationFR8 papers
- Donostia International Physics CenterES7 papers
- Hitachi Global Storage Technologies (United States)US7 papers
- CEA GrenobleFR6 papers
- Texas A&M UniversityUS6 papers
- University of ExeterGB6 papers
- Chinese Academy of SciencesCN5 papers
22 papers · 1 filter
Building Multi lingual TTS using Cross Lingual Voice Conversion
Qinghua Sun, Kenji Nagamatsu
In this paper we propose a new cross-lingual Voice Conversion (VC) approach which can generate all speech parameters (MCEP, LF0, BAP) from one DNN model using PPGs (Phonetic Poster…
Stimulated emission depletion spectroscopy of color centers in hexagonal boron nitride
Ralph N. E. Malein, Prince Khatri, Andrew J. Ramsay +1
We demonstrate the use of Stimulated Emission Depletion (STED) spectroscopy to map the electron-optical-phonon sideband of the ground state of the radiative transition of color cen…
Electrical control of the -tensor of a single hole in a silicon MOS quantum dot
S. D. Liles, F. Martins, D. S. Miserev +11
Single holes confined in semiconductor quantum dots are a promising platform for spin qubit technology, due to the electrical tunability of the -factor of holes. However, the un…
Challenges of Applying Deep Reinforcement Learning in Dynamic Dispatching
Hamed Khorasgani, Haiyan Wang, Chetan Gupta
Dynamic dispatching aims to smartly allocate the right resources to the right place at the right time. Dynamic dispatching is one of the core problems for operations optimization i…
Crack Detection as a Weakly-Supervised Problem: Towards Achieving Less Annotation-Intensive Crack Detectors
Yuki Inoue, Hiroto Nagayoshi
Automatic crack detection is a critical task that has the potential to drastically reduce labor-intensive building and road inspections currently being done manually. Recent studie…
Qubit-excitation-based adaptive variational quantum eigensolver
Yordan S. Yordanov, V. Armaos, Crispin H. W. Barnes +1
Molecular simulations with the variational quantum eigensolver (VQE) are a promising application for emerging noisy intermediate-scale quantum computers. Constructing accurate mole…
Cycle-Contrast for Self-Supervised Video Representation Learning
Quan Kong, Wenpeng Wei, Ziwei Deng +2
We present Cycle-Contrastive Learning (CCL), a novel self-supervised method for learning video representation. Following a nature that there is a belong and inclusion relation of v…
Deep Autoencoding GMM-based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-parameter Optimization
Harsh Purohit, Ryo Tanabe, Takashi Endo +3
Failures or breakdowns in factory machinery can be costly to companies, so there is an increasing demand for automatic machine inspection. Existing approaches to acoustic signal-ba…
Conditions tighter than noncommutation needed for nonclassicality
David R. M. Arvidsson-Shukur, Jacob Chevalier Drori, Nicole Yunger Halpern
Kirkwood discovered in 1933, and Dirac discovered in 1945, a representation of quantum states that has undergone a renaissance recently. The Kirkwood-Dirac (KD) distribution has be…
Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
Chi Zhang, Philip Odonkor, Shuai Zheng +3
Dynamic dispatching is one of the core problems for operation optimization in traditional industries such as mining, as it is about how to smartly allocate the right resources to t…
Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones
Shota Horiguchi, Yusuke Fujita, Kenji Nagamatsu
A novel framework for meeting transcription using asynchronous microphones is proposed in this paper. It consists of audio synchronization, speaker diarization, utterance-wise spee…
Pair emission from a relativistic domain wall in antiferromagnets
Gen Tatara, Collins Ashu Akosa, Rubén M. Otxoa de Zuazola
Magnon emission and excitation by a relativistic domain wall at a constant velocity in antiferromagnet is theoretically studied. A pair emission due to a quadratic magnon coupling…
DeepCO: Offline Combinatorial Optimization Framework Utilizing Deep Learning
Wenpeng Wei, Toshiko Aizono
Combinatorial optimization serves as an essential part in many modern industrial applications. A great number of the problems are offline setting due to safety and/or cost issues.…
Channel-Level Variable Quantization Network for Deep Image Compression
Zhisheng Zhong, Hiroaki Akutsu, Kiyoharu Aizawa
Deep image compression systems mainly contain four components: encoder, quantizer, entropy model, and decoder. To optimize these four components, a joint rate-distortion framework…
Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals
Jing Shi, Xuankai Chang, Pengcheng Guo +5
Neural sequence-to-sequence models are well established for applications which can be cast as mapping a single input sequence into a single output sequence. In this work, we focus…
Speaker-Conditional Chain Model for Speech Separation and Extraction
Jing Shi, Jiaming Xu, Yusuke Fujita +2
Speech separation has been extensively explored to tackle the cocktail party problem. However, these studies are still far from having enough generalization capabilities for real s…
Health Indicator Forecasting for Improving Remaining Useful Life Estimation
Qiyao Wang, Ahmed Farahat, Chetan Gupta +1
Prognostics is concerned with predicting the future health of the equipment and any potential failures. With the advances in the Internet of Things (IoT), data-driven approaches fo…
Neural Speaker Diarization with Speaker-Wise Chain Rule
Yusuke Fujita, Shinji Watanabe, Shota Horiguchi +3
Speaker diarization is an essential step for processing multi-speaker audio. Although an end-to-end neural diarization (EEND) method achieved state-of-the-art performance, it is li…
Unsupposable Test-data Generation for Machine-learned Software
Naoto Sato, Hironobu Kuruma, Hideto Ogawa
As for software development by machine learning, a trained model is evaluated by using part of an existing dataset as test data. However, if data with characteristics that differ f…
End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors
Shota Horiguchi, Yusuke Fujita, Shinji Watanabe +2
End-to-end speaker diarization for an unknown number of speakers is addressed in this paper. Recently proposed end-to-end speaker diarization outperformed conventional clustering-b…
Minor-embedding heuristics for large-scale annealing processors with sparse hardware graphs of up to 102,400 nodes
Yuya Sugie, Yuki Yoshida, Normann Mertig +7
Minor embedding heuristics have become an indispensable tool for compiling problems in quadratically unconstrained binary optimization (QUBO) into the hardware graphs of quantum an…
Entanglement generation via power-of-SWAP operations between dynamic electron-spin qubits
Hugo V. Lepage, Aleksander A. Lasek, David R. M. Arvidsson-Shukur +1
Surface acoustic waves (SAWs) can create moving quantum dots in piezoelectric materials. Here we show how electron-spin qubits located on dynamic quantum dots can be entangled. Pre…