270 research outputs found
Reinforcement Learning of Speech Recognition System Based on Policy Gradient and Hypothesis Selection
Speech recognition systems have achieved high recognition performance for
several tasks. However, the performance of such systems is dependent on the
tremendously costly development work of preparing vast amounts of task-matched
transcribed speech data for supervised training. The key problem here is the
cost of transcribing speech data. The cost is repeatedly required to support
new languages and new tasks. Assuming broad network services for transcribing
speech data for many users, a system would become more self-sufficient and more
useful if it possessed the ability to learn from very light feedback from the
users without annoying them. In this paper, we propose a general reinforcement
learning framework for speech recognition systems based on the policy gradient
method. As a particular instance of the framework, we also propose a hypothesis
selection-based reinforcement learning method. The proposed framework provides
a new view for several existing training and adaptation methods. The
experimental results show that the proposed method improves the recognition
performance compared to unsupervised adaptation.Comment: 5 pages, 6 figure
Streaming Target-Speaker ASR with Neural Transducer
Although recent advances in deep learning technology have boosted automatic
speech recognition (ASR) performance in the single-talker case, it remains
difficult to recognize multi-talker speech in which many voices overlap. One
conventional approach to tackle this problem is to use a cascade of a speech
separation or target speech extraction front-end with an ASR back-end. However,
the extra computation costs of the front-end module are a critical barrier to
quick response, especially for streaming ASR. In this paper, we propose a
target-speaker ASR (TS-ASR) system that implicitly integrates the target speech
extraction functionality within a streaming end-to-end (E2E) ASR system, i.e.
recurrent neural network-transducer (RNNT). Our system uses a similar idea as
adopted for target speech extraction, but implements it directly at the level
of the encoder of RNNT. This allows TS-ASR to be realized without placing extra
computation costs on the front-end. Note that this study presents two major
differences between prior studies on E2E TS-ASR; we investigate streaming
models and base our study on Conformer models, whereas prior studies used
RNN-based systems and considered only offline processing. We confirm in
experiments that our TS-ASR achieves comparable recognition performance with
conventional cascade systems in the offline setting, while reducing computation
costs and realizing streaming TS-ASR.Comment: Accepted to Interspeech 202
Strain Rate Concentration Factor for Double-Edge-Notched Specimens Subjected to High Speed Tensile Loads
Engineering plastics provide superior performance to ordinary plastics for wide range of the use. For polymer materials, dynamic stress and strain rate may be major factors to be considered when the strength is evaluated. Recently, high speed tensile test is being recognized as a standard testing method to confirm the strength under dynamic loads. In this study, therefore, high speed tensile test is analyzed by the finite element method; then, the maximum dynamic stress and strain rate are discussed with varying the tensile speed and maximum forced displacement. The strain rate concentration factor found to be constant independent of tensile speed, which is defined Ktέ as the maximum strain rate appeared at the notch root over the average nominal strain rate at the minimum section. The maximum strain rate is controlled by the tensile speed alone independent of the magnitude of the forced displacement. It is found that the difference between static and dynamic maximum stress concentration (σmax-σst) at the notch root is proportional to the tensile speed when u/t≦5000mm/s.13th International Conference on Fracture, June 16–21, 2013, Beijing, Chin
Improving Eye Motion Sequence Recognition Using Electrooculography Based on Context-Dependent HMM
Eye motion-based human-machine interfaces are used to provide a means of communication for those who can move nothing but their eyes because of injury or disease. To detect eye motions, electrooculography (EOG) is used. For efficient communication, the input speed is critical. However, it is difficult for conventional EOG recognition methods to accurately recognize fast, sequentially input eye motions because adjacent eye motions influence each other. In this paper, we propose a context-dependent hidden Markov model- (HMM-) based EOG modeling approach that uses separate models for identical eye motions with different contexts. Because the influence of adjacent eye motions is explicitly modeled, higher recognition accuracy is achieved. Additionally, we propose a method of user adaptation based on a user-independent EOG model to investigate the trade-off between recognition accuracy and the amount of user-dependent data required for HMM training. Experimental results show that when the proposed context-dependent HMMs are used, the character error rate (CER) is significantly reduced compared with the conventional baseline under user-dependent conditions, from 36.0 to 1.3%. Although the CER increases again to 17.3% when the context-dependent but user-independent HMMs are used, it can be reduced to 7.3% by applying the proposed user adaptation method
Development of an adiabatic demagnetization refrigerator for X-ray microcalorimeter operations
金沢大学理工研究域数物科学系An X-ray microcalorimeter is a non-dispersive spectrometer that measures the energy of an incident X-ray photon as a temperature rise. Operated at < 0.1 K, it achieves very high resolving power. We are developing X-ray microcalorimeters for future γ-ray burst observations, and are now setting up a compact adiabatic demagnetization refrigerator (ADR) for X-ray microcalorimeter operations. We fabricated a paramagnetic salt pill, and integrated it with a superconducting magnet and a heat-switch in a dedicated He cryostat. By applying a magnetic field of 2.6 T at the bath temperature of 1.8 K, it achieved 0.1 K. The attainable temperature and the hold time were, however, limited due to unexpected heat load. We also successfully measured a resistance-temperature characteristics of a superconducting transition edge. © 2010 American Institute of Physics
Astrocytic dysfunction induced by ABCA1 deficiency causes optic neuropathy
Astrocyte abnormalities have received great attention for their association with various diseases in the brain but not so much in the eye. Recent independent genome-wide association studies of glaucoma, optic neuropathy characterized by retinal ganglion cell (RGC) degeneration, and vision loss found that single-nucleotide polymorphisms near the ABCA1 locus were common risk factors. Here, we show that Abca1 loss in retinal astrocytes causes glaucoma-like optic neuropathy in aged mice. ABCA1 was highly expressed in retinal astrocytes in mice. Thus, we generated macroglia-specific Abca1-deficient mice (Glia-KO) and found that aged Glia-KO mice had RGC degeneration and ocular dysfunction without affected intraocular pressure, a conventional risk factor for glaucoma. Single-cell RNA sequencing revealed that Abca1 deficiency in aged Glia-KO mice caused astrocyte-triggered inflammation and increased the susceptibility of certain RGC clusters to excitotoxicity. Together, astrocytes play a pivotal role in eye diseases, and loss of ABCA1 in astrocytes causes glaucoma-like neuropathy
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Pushing the Envelope—Aside
Despite successes, there are still significant limitations to speech recognition performance, particularly for conversational speech and/or for speech with significant acoustic degradations from noise or reverberation. For this reason, authors have proposed methods that incorporate different (and larger) analysis windows, which are described in this article. Note in passing that we and many others have already taken advantage of processing techniques that incorporate information over long time ranges, for instance for normalization (by cepstral mean subtraction as stated in B. Atal (1974) or relative spectral analysis (RASTA) based in H. Hermansky and N. Morgan (1994)). They also have proposed features that are based on speech sound class posterior probabilities, which have good properties for both classification and stream combination
The ASTRO-H X-ray Observatory
The joint JAXA/NASA ASTRO-H mission is the sixth in a series of highly
successful X-ray missions initiated by the Institute of Space and Astronautical
Science (ISAS). ASTRO-H will investigate the physics of the high-energy
universe via a suite of four instruments, covering a very wide energy range,
from 0.3 keV to 600 keV. These instruments include a high-resolution,
high-throughput spectrometer sensitive over 0.3-2 keV with high spectral
resolution of Delta E < 7 eV, enabled by a micro-calorimeter array located in
the focal plane of thin-foil X-ray optics; hard X-ray imaging spectrometers
covering 5-80 keV, located in the focal plane of multilayer-coated, focusing
hard X-ray mirrors; a wide-field imaging spectrometer sensitive over 0.4-12
keV, with an X-ray CCD camera in the focal plane of a soft X-ray telescope; and
a non-focusing Compton-camera type soft gamma-ray detector, sensitive in the
40-600 keV band. The simultaneous broad bandpass, coupled with high spectral
resolution, will enable the pursuit of a wide variety of important science
themes.Comment: 22 pages, 17 figures, Proceedings of the SPIE Astronomical
Instrumentation "Space Telescopes and Instrumentation 2012: Ultraviolet to
Gamma Ray
Hitomi (ASTRO-H) X-ray Astronomy Satellite
The Hitomi (ASTRO-H) mission is the sixth Japanese x-ray astronomy satellite developed by a large international collaboration, including Japan, USA, Canada, and Europe. The mission aimed to provide the highest energy resolution ever achieved at E > 2 keV, using a microcalorimeter instrument, and to cover a wide energy range spanning four decades in energy from soft x-rays to gamma rays. After a successful launch on February 17, 2016, the spacecraft lost its function on March 26, 2016, but the commissioning phase for about a month provided valuable information on the onboard instruments and the spacecraft system, including astrophysical results obtained from first light observations. The paper describes the Hitomi (ASTRO-H) mission, its capabilities, the initial operation, and the instruments/spacecraft performances confirmed during the commissioning operations for about a month
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