5,126 research outputs found
Disentangled Feature Learning for Real-Time Neural Speech Coding
Recently end-to-end neural audio/speech coding has shown its great potential
to outperform traditional signal analysis based audio codecs. This is mostly
achieved by following the VQ-VAE paradigm where blind features are learned,
vector-quantized and coded. In this paper, instead of blind end-to-end
learning, we propose to learn disentangled features for real-time neural speech
coding. Specifically, more global-like speaker identity and local content
features are learned with disentanglement to represent speech. Such a compact
feature decomposition not only achieves better coding efficiency by exploiting
bit allocation among different features but also provides the flexibility to do
audio editing in embedding space, such as voice conversion in real-time
communications. Both subjective and objective results demonstrate its coding
efficiency and we find that the learned disentangled features show comparable
performance on any-to-any voice conversion with modern self-supervised speech
representation learning models with far less parameters and low latency,
showing the potential of our neural coding framework.Comment: Submitted to ICASSP202
Dual Skipping Networks
Inspired by the recent neuroscience studies on the left-right asymmetry of
the human brain in processing low and high spatial frequency information, this
paper introduces a dual skipping network which carries out coarse-to-fine
object categorization. Such a network has two branches to simultaneously deal
with both coarse and fine-grained classification tasks. Specifically, we
propose a layer-skipping mechanism that learns a gating network to predict
which layers to skip in the testing stage. This layer-skipping mechanism endows
the network with good flexibility and capability in practice. Evaluations are
conducted on several widely used coarse-to-fine object categorization
benchmarks, and promising results are achieved by our proposed network model.Comment: CVPR 2018 (poster); fix typ
The Semantics and Pragmatics of the Quasi-logical Use of yòu in Mandarin Chinese
This paper focuses on the quasi-logical use of yòu (又) ‘again’ in naturally occurring conversation. It is argued that such a usage of yòu not only keeps its generalised conjunctive meaning, whose left conjunct can be either explicitly present or omitted, but also contributes to inducing pragmatic inferences. Since the logically encoded meaning of yòu and the presuppositional meaning it engenders fail to provide a coherent interpretation of yòu in a negation context, there is a need to backtrack and accommodate an implicit proposition as the premise for inferring the implicature of that utterance, i.e. a conditional. We also argue that what really invites the said abductive inference is the specific construction of [yòu + neg + right conjunct], rather than the adverb yòu per se
Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy
With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs
Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy
With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs
Overview of Contraindicated Chinese Medicines for Pregnancy
Chinese medicines should be classified into drugs, which have both beneficial and harmful effects. For centuries, Chinese medicines have been widely used to relieve many symptoms and to treat complications during pregnancy. It is not clear how safe the Chinese medicines are being used during pregnancy and if there is any adverse effects to embryo-fetal development and prenatal and postnatal growth. Some Chinese medicines are indicated that they cannot be used in pregnancy. In this chapter, we will conduct a systematic review to summarize and characterize in details the Chinese medicines classified as contraindicated, not recommended and cautiously used for pregnancy in most updated version of Pharmacopeia of the People’s Republic of China. Clinical reports including clinical trials, case reports, case series and animal studies including short-term and long-term toxicity, specific organ toxicity and different species of the Chinese medicines will be studied. Unlike those pharmaceutical drugs not recommend for use during pregnancy because of known or suspected adverse or teratogenic effects evident by animal studies and/or clinical trials, most of the Chinese medicines were utilized for long history in culture which, however, has very limited scientific data regarding the adverse pregnant outcomes
Multiple Unpinned Dirac Points in Group-Va Single-layers with Phosphorene Structure
Emergent Dirac fermion states underlie many intriguing properties of
graphene, and the search for them constitute one strong motivation to explore
two-dimensional (2D) allotropes of other elements. Phosphorene, the ultrathin
layers of black phosphorous, has been a subject of intense investigations
recently, and it was found that other group-Va elements could also form 2D
layers with similar puckered lattice structure. Here, by a close examination of
their electronic band structure evolution, we discover two types of Dirac
fermion states emerging in the low-energy spectrum. One pair of (type-I) Dirac
points is sitting on high-symmetry lines, while two pairs of (type-II) Dirac
points are located at generic -points, with different anisotropic
dispersions determined by the reduced symmetries at their locations. Such
fully-unpinned (type-II) 2D Dirac points are discovered for the first time. In
the absence of spin-orbit coupling, we find that each Dirac node is protected
by the sublattice symmetry from gap opening, which is in turn ensured by any
one of three point group symmetries. The spin-orbit coupling generally gaps the
Dirac nodes, and for the type-I case, this drives the system into a quantum
spin Hall insulator phase. We suggest possible ways to realize the unpinned
Dirac points in strained phosphorene.Comment: 30 pages, 6 figure
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