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

Atrial natriuretic peptide promotes cardiomyocyte survival by cGMP-dependent nuclear accumulation of zyxin and Akt

Journal ArticleThis study delineates a mechanism for antiapoptotic signaling initiated by atrial natriuretic peptide (ANP) stimulation leading to elevation of cGMP levels and subsequent nuclear accumulation of Akt kinase associated with zyxin, a cytoskeletal LIM-domain protein. Nuclear targeting of zyxin induces resistance to cell death coincident with nuclear accumulation of activated Akt

Effect of Threats to Property Rights on Economic Performance of the Manufacturing Sector of Indian States

We examine the effect of threats to property rights on the economic performance of the manufacturing sector of Indian states. We construct indices of the threats from data on crime against property rights. Our estimation results show that not only threats to private property, but also threats to contracts adversely affect the performance of India's manufacturing sector.Property right, Contract, Gross value added, Capital labor ratio, TFP

Macroscopic thermodynamic reversibility in quantum many-body systems

The resource theory of thermal operations, an established model for small-scale thermodynamics, provides an extension of equilibrium thermodynamics to nonequilibrium situations. On a lattice of any dimension with any translation-invariant local Hamiltonian, we identify a large set of translation-invariant states that can be reversibly converted to and from the thermal state with thermal operations and a small amount of coherence. These are the spatially ergodic states, i.e., states that have sharp statistics for any translation-invariant observable, and mixtures of such states with the same thermodynamic potential. As an intermediate result, we show for a general state that if the gap between the min- and the max-relative entropies to the thermal state is small, then the state can be approximately reversibly converted to and from the thermal state with thermal operations and a small source of coherence. Our proof provides a quantum version of the Shannon-McMillan-Breiman theorem for the relative entropy and a quantum Stein’s lemma for ergodic states and local Gibbs states. Our results provide a strong link between the abstract resource theory of thermodynamics and more realistic physical systems as we achieve a robust and operational characterization of the emergence of a thermodynamic potential in translation-invariant lattice systems

A Study on Deep CNN Structures for Defect Detection From Laser Ultrasonic Visualization Testing Images

The importance of ultrasonic nondestructive testing has been increasing in recent years, and there are high expectations for the potential of laser ultrasonic visualization testing, which combines laser ultrasonic testing with scattered wave visualization technology. Even if scattered waves are visualized, inspectors still need to carefully inspect the images. To automate this, this paper proposes a deep neural network for automatic defect detection and localization in LUVT images. To explore the structure of a neural network suitable to this task, we compared the LUVT image analysis problem with the generic object detection problem. Numerical experiments using real-world data from a SUS304 flat plate showed that the proposed method is more effective than the general object detection model in terms of prediction performance. We also show that the computational time required for prediction is faster than that of the general object detection model

A case of gastropericardial fistula of a gastric tube after esophagectomy: a case report and review

A 65-year-old man who had received an esophagectomy 10 years earlier was admitted to our hospital for right chest pain. Preoperative examinations showed pneumopericardium, a retrosternal gastric tube, and an active gastric tube ulcer. We diagnosed gastropericardial fistula of the gastric tube ulcer. Emergency surgery included lavage and drainage of the pericardial cavity and plombage of the rectus abdominis muscle flap to the posterior space of the gastric tube. Total parental nutrition and/or enteric nutrition were provided. Due to minor leakage from the ulcer, the patient could start oral intake on the postoperative 49th day, and was discharged from the hospital on the postoperative 86th day after physical rehabilitation. He has been free from complications for more than 33 months after surgery. Here, we review the literature and discuss the etiology and treatment of choice for this rare yet lethal complication in the follow-up after esophagectomy