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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 18 of 18  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IA 2023-09-21
Hokkaido Hokkaido Univeristy
(Primary: On-site, Secondary: Online)
Extracting context from external events using auxiliary information from network traffic data
Eilaf M.A Babai, Koji Okamura (Kyushu Univ.) IA2023-13
Network traffic flow data is the main source of information about the network status, and it is constantly monitored to ... [more] IA2023-13
PRMU, IPSJ-CVIM 2022-03-11
Online Online Context free grammar with tree structure analysis for online handwritten mathematical expression recognition
Naruki Kitashima, Cuong Tuan Nguyen, Ikuko Shimizu, Masaki Nakagawa (TUAT) PRMU2021-76
In mathematics exams, descriptive questions are effective for measuring the comprehension of examinees, but marking hand... [more] PRMU2021-76
2021-03-03 Online Online An evaluation on incremental addition of new portable device storing positions under realistic usage scenarios
Mitsuaki Saito, Kaori Fujinami (TUAT)
With the spread of portable devices in recent years, work is being actively conducted to recognize the position of the d... [more]
EA, SP, SIP 2016-03-29
Oita Beppu International Convention Center B-ConPlaza [Poster Presentation] An experimental study of designing context labels for infant-directed storytelling speech synthesis
Kyota Hyakutake, Daisuke Saito, Nobuaki Minematsu (UTokyo) EA2015-112 SIP2015-161 SP2015-140
Context labels for infant-directed storytelling speech synthesis are investigated. After collecting one-hour storytellin... [more] EA2015-112 SIP2015-161 SP2015-140
SP 2015-10-15
Hyogo Kobe Univ. A study on quick model training in HMM-based speech synthesis
Shuhei Yamada, Takashi Nose, Akinori Ito (Tohoku Univ.) SP2015-64
In this paper, we propose an alternative model training technique using speaker-independent monophone models and decisio... [more] SP2015-64
SP, IPSJ-MUS 2014-05-25
Tokyo   Text-to-speech prosody synthesis based on probabilistic model for F0 contour
Kento Kadowaki, Tatsuma Ishihara, Nobukatsu Hojo (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/NTT) SP2014-28
This paper deals with the problem of generating the fundamental frequency (F0) contour of speech from a text input for t... [more] SP2014-28
SC 2014-01-10
Tokyo NII Context Aware Web Service Similarity and Visualization
Banage T. G. S. Kumara, Incheon Paik, Hiroki Ohashi, Yuichi Yaguchi (Univ. of Aizu) SC2013-18
Web service similarity calculation is a major challenge in service computing research. There are several methods used in... [more] SC2013-18
SP, IPSJ-SLP 2013-12-20
Tokyo   Application of HMM-Based Speech Synthesis Techniques to a Singing Style Synthesis Job Plugin
Makoto Tachibana, Keijiro Saino, Yuji Hisaminato (Yamaha Corp) SP2013-94
Recent HMM-based speech synthesis systems have the capability to control speaker/style characteristics by statistically ... [more] SP2013-94
SP 2012-11-08
Miyagi Ichibancho Lobby, Tohoku Institute of Technology Improvements of HMM-based speech synthesis using rich context models
Shinnosuke Takamichi, Tomoki Toda (NAIST), Yoshinori Shiga (NICT), Sakriani Sakti, Graham Neubig, Satoshi Nakamura (NAIST) SP2012-78
In the traditional HMM-based speech synthesis, generated speech parameters tend to be excessively smoothed.
To allevia... [more]
SP 2012-11-08
Miyagi Ichibancho Lobby, Tohoku Institute of Technology Prosody Generation based on HMM using Tow-stage Clustering
Yasuyuki Mitsui, Reishi Kondo, Masanori Kato (NEC) SP2012-80
HMM-based speech synthesis can generate highly natural prosody, but there is a problem that the pitch patterns represent... [more] SP2012-80
Miyazaki Miyazaki Seagia Object Data Configuration and Performance Evaluation in User Context Based Menu Recommendation Service.
Yousuke Tsuda, Maho Sakuma, Toshihiro Nishizono (Nihon Univ) NS2011-274
This paper presents implementation and evaluation of a menu recommendation system using high dimensional user context de... [more] NS2011-274
EA, SIP, SP 2011-05-13
Osaka Ritsumeikan Univ. Performance evaluation of contexts for conversational speech synthesis using Corpus of Spontaneous Japanese
Tomoki Koriyama, Takashi Nose, Takao Kobayashi (Tokyo Tech) EA2011-27 SIP2011-27 SP2011-27
This paper proposes an extended context set for generating the prosodic variability of spontaneous speech in HMM-based c... [more] EA2011-27 SIP2011-27 SP2011-27
PRMU 2011-03-10
Ibaraki   Simultaneous Optimization of Context Clustering and GMM for Offline Handwritten Word Recognition Using HMM
Tomoyuki Hamamura (Toshiba/Univ. of Tokyo), Bunpei Irie (Toshiba), Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (Univ. of Tokyo) PRMU2010-244
Context-dependent HMM is commonly used in speech recognition. The model can be realized by two ways: context clustering ... [more] PRMU2010-244
Okinawa Okinawa Convention Center Evaluation of Privacy Preservation Recommendation Based on Bayesian Networks
Shogo Hachiya, Toshihiro Nishizono (Nihon Univ.) NS2010-242
This paper proposes a method for constructing privacy-preserving recommendation models for content-based filtering. Afte... [more] NS2010-242
SP, NLC 2008-12-10
Tokyo Waseda Univ. Bayesian Context Clustering Using Cross Validation for HMM-Based Speech Synthesis
Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Institute of Technology) NLC2008-36 SP2008-91
This paper proposes a prior distribution determination technique using cross validation for HMM-based speech synthesis b... [more] NLC2008-36 SP2008-91
SP, NLC 2008-12-10
Tokyo Waseda Univ. Tying covariance parameters for HMM-based speech synthesis
Keiichiro Oura, Heiga Zen, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda (Nagoya Inusitute of Technology) NLC2008-60 SP2008-115
In this paper, we proposed a tying covariance technique in hidden Markov model (HMM) basedspeech
synthesis system. In r... [more]
NLC2008-60 SP2008-115
SP, NLC 2008-12-10
Tokyo Waseda Univ. Speech Recognition Based on Statistical Models Including Multiple Decision Trees
Sayaka Shiota, Kei Hashimoto, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda (Nagoya Institute of Technology) NLC2008-61 SP2008-116
This paper proposes a speech recoginition technique using multiple decision trees. In the use of context dependent model... [more] NLC2008-61 SP2008-116
Toyama Toyama Prefectural University Acoustic Modeling Based on Model Structure Annealing for Speech Recognition
Sayaka Shiota, Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda (Nitech) SP2007-35
This paper proposes a joint optimization technique of phonetic decision trees and state sequences for HMM-based speech r... [more] SP2007-35
 Results 1 - 18 of 18  /   
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