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Hiroki Mori

Researcher at Utsunomiya University

Publications -  64
Citations -  318

Hiroki Mori is an academic researcher from Utsunomiya University. The author has contributed to research in topics: Speech synthesis & Mandarin Chinese. The author has an hindex of 7, co-authored 59 publications receiving 245 citations.

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Constructing a spoken dialogue corpus for studying paralinguistic information in expressive conversation and analyzing its statistical/acoustic characteristics

TL;DR: To stimulate expressively-rich and vivid conversation, the ''4-frame cartoon sorting task'' was devised and the perceived emotional states of speakers can be accurately estimated from the speech parameters in most cases.
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Sildenafil reduces pulmonary vascular resistance in single ventricular physiology

TL;DR: Sildenafil reduced PVR in patients with single ventricle physiology and increased exercise capacity and improved NYHA functional class in patients after a Fontan operation, implying that pulmonary vasodilation is a potential therapeutic target in selected patients with elevated PVR with single Ventricular physiology.
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Global strain and dyssynchrony of the single ventricle predict adverse cardiac events after the Fontan procedure: Analysis using feature-tracking cine magnetic resonance imaging.

TL;DR: GLS and the dyssynchrony index found using CMR-FT are independent predictors of MACE for adolescent patients after the Fontan procedure and provide information regarding risk stratification beyond clinical parameters and biomarkers.
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Development of a Compact Wireless Laplacian Electrode Module for Electromyograms and Its Human Interface Applications

TL;DR: Finger movement detection experiments showed that each finger movement was more clearly detectable when comparing to EMGs recorded with conventional electrodes, suggesting that the Laplacian electrode module is more suitable for detecting the timing of finger movement during typing.
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Dimensional paralinguistic information control based on multiple-regression HSMM for spontaneous dialogue speech synthesis with robust parameter estimation

TL;DR: This paper describes spontaneous dialogue speech synthesis based on the multiple regression hidden semi-Markov model (MRHSMM), which enables users to specify paralinguistic information of synthesized speech with a dimensional representation, and confirmed that the naturalness of synthesizer speech was improved by applying the MAP estimation for regression matrices.