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

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