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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 106 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
09:25
Okinawa   Stable Estimation Method of Spatial Correlation Matrices for Multi-channel NMF
Yuuki Tachioka (Denso IT Lab) EA2017-103 SIP2017-112 SP2017-86
Multi-channel non-negative matrix factorization (MNMF) achieves a high sound source separation performance but its initi... [more] EA2017-103 SIP2017-112 SP2017-86
pp.7-12
SIP, EA, SP, MI
(Joint) [detail]
2018-03-20
09:00
Okinawa   [Poster Presentation] Perceptual influence of spectral envelope and aperiodicity quantization for encoding high-quality speech
Genta Miyashita, Masanori Morise (Univ. of Yamanashi) EA2017-145 SIP2017-154 SP2017-128
In this paper, we investigate the relationship between the degradation of sound quality and the parameter quantization i... [more] EA2017-145 SIP2017-154 SP2017-128
pp.241-244
EA 2018-02-16
13:10
Hiroshima Pref. Univ. Hiroshima The effect of increasing the number of channels with multi-channel non-negative matrix factorization for noisy speech recognition
Takanobu Uramoto (Oita Univ.), Youhei Okato, Toshiyuki Hanazawa (Mitsubishi Electric), Iori Miura, Shingo Uenohara, Ken'ich Furuya (Oita Univ.) EA2017-99
Nonnegative Matrix Factorization (NMF) factorizes a non-negative matrix into two non-negative matrices. In the field of ... [more] EA2017-99
pp.33-38
SP, ASJ-H 2018-01-20
13:25
Tokyo The University of Tokyo A study on statistical speech synthesis based on GP-DNN hybrid model
Tomoki Koriyama, Takao Kobayashi (Tokyo Tech) SP2017-67
We propose a novel approach to Gaussian process regression (GPR)-based speech synthesis
in this paper.
Since the conve... [more]
SP2017-67
pp.5-10
SP, ASJ-H 2018-01-20
13:50
Tokyo The University of Tokyo DNN Based Voice Conversion Method Considering Outputs of Multiple Networks
Takuya Fujioka, Sun Qinghua (Hitachi) SP2017-68
In many conventional statistical voice conversion methods, the relations of source and target speech on all frames are e... [more] SP2017-68
pp.11-15
SP, ASJ-H 2018-01-20
14:55
Tokyo The University of Tokyo [Poster Presentation] Influence of frame shift in speech parameters on sound quality by high-quality speech analysis/synthesis system
Genta Miyashita, Masanori Morise (Yamanashi Univ.) SP2017-72
Sound quality deterioration occurs when analyzing and synthesizing high--quality speech by using a vocoder.
We conduct ... [more]
SP2017-72
pp.35-38
SP, SIP, EA 2017-03-01
12:40
Okinawa Okinawa Industry Support Center [Poster Presentation] An investigation of speaker adaptation method for DNN-based speech synthesis using speaker codes
Nobukatsu Hojo, Yusuke Ijima (NTT) EA2016-108 SIP2016-163 SP2016-103
In this work, we conducted objective evaluation experiments on the conventional speaker adaptation methods for DNN-based... [more] EA2016-108 SIP2016-163 SP2016-103
pp.147-152
SP 2017-01-21
16:35
Tokyo The University of Tokyo Simultaneous modeling of acoustic feature sequences and its temporal structures for DNN-based speech synthesis
Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) SP2016-76
In statistical parametric speech synthesis, a hidden Markov model (HMM) is widely used as an acoustic model. Recently, d... [more] SP2016-76
pp.71-76
EA, EMM 2016-11-18
14:05
Oita Compal Hall (Oita) Basic Study of the Sound Quality Improvement using the Signal Enhancement of the Sound from inside of the Body
Masatoshi Tsukiashi, Yoichi Midorikawa, Masanori Akita (Oita Univ.) EA2016-64 EMM2016-70
We have studied the detection of sleepiness or the detection of the change of feelings using NAM microphones. NAM microp... [more] EA2016-64 EMM2016-70
pp.95-100
WIT 2016-10-16
15:35
Saga Karatsu Royal Hotel (Saga pref.) Study on subjective impressions and acoustic characteristics of elderly speech
Shuhei Takemori, Mitsunori Mizumachi (KIT) WIT2016-38
There are a variety of works concerning subjective impressions of elderly speech, and hoarseness is commonly selected as... [more] WIT2016-38
pp.29-34
EA, ASJ-H, IPSJ-MUS [detail] 2016-10-14
14:30
Ishikawa Noto Omakidai (Nanao) Study on speech transmission index using models of modulation transfer function
Yuta Kashihara, Masashi Unoki (JAIST) EA2016-33
Room impluse response (RIR) is composed of three parts: direct sound, early reverberation, and late reverberation.
It ... [more]
EA2016-33
pp.13-18
EA, ASJ-H 2016-08-09
15:25
Miyagi Tohoku Gakuin Univ., Tagajo Campus EA2016-24 This talk describes the research achievements of the late Prof. Ken’iti Kido in speech research. In order to apply a spe... [more] EA2016-24
pp.25-30
SP 2016-01-14
13:00
Kanagawa Sunpian Kawasaki [Invited Talk] Articulatory controllable statistical parametric speech synthesis using EMA data
Junichi Yamagishi (NII/Univ. Edinburgh) SP2015-88
This paper describes speech processing work in which articulator movements are used in conjunction with the acoustic spe... [more] SP2015-88
pp.19-24
NLC, IPSJ-NL, SP, IPSJ-SLP
(Joint) [detail]
2015-12-02
11:15
Aichi Nagoya Inst of Tech. Evaluation and Analysis of Duration Correction for Non-Native Speech Based on Waveform Modification
Shinya Kura, Shinnosuke Takamichi (NAIST), Tomoki Toda (NAIST/Nagoya Univ.), Graham Neubig, Sakriani Sakti, Satoshi Nakamura (NAIST) SP2015-73
There are several attempts at correcting durational patterns of non-native speech towards language learning. One of the ... [more] SP2015-73
pp.19-24
NLC, IPSJ-NL, SP, IPSJ-SLP
(Joint) [detail]
2015-12-02
13:55
Aichi Nagoya Inst of Tech. Automation of high performance system building for large vocabulary speech recognition using evolution strategy with pareto optimality
Takafumi Moriya, Tomohiro Tanaka, Takahiro Shinozaki (Tokyo Tech), Shinji Watanabe (MERL), Kevin Duh (NAIST) SP2015-75
The performance of speech recognition tasks can be significantly improved by the use of deep neural networks (DNN). Howe... [more] SP2015-75
pp.31-36
SP, IPSJ-SLP
(Joint)
2015-07-16
16:20
Nagano Katakura Suwako Hotel Sequence Discriminative Training for Low-Rank Deep Neural Networks
Yuuki Tachioka (Mitsubishi Electric), Shinji Watanabe, Jonathan Le Roux, John Hershey (MERL) SP2015-39
Deep neural network (DNN) acoustic models outperform conventional Gaussian mixture model (GMM) but the number of paramet... [more] SP2015-39
pp.19-24
SP, IPSJ-SLP
(Joint)
2015-07-16
17:50
Nagano Katakura Suwako Hotel Speaker Adaptation Technique for Speech Recognition using a Feature Augmentation Framework
Hiroshi Fujimura, Takashi Masuko (TOSHIBA) SP2015-42
Deep Neural Networks (DNNs) are powerful machine learning models.Nevertheless, the performance degrades for out-of domai... [more] SP2015-42
pp.37-42
SIP, EA, SP 2015-03-02
11:40
Okinawa   Optimization of impulse responses for model training in reverberant speech recognition
Takahiro Fukumori, Masato Nakayama, Takanobu Nishiura, Yoichi Yamashita (Ritsumeikan Univ.) EA2014-78 SIP2014-119 SP2014-141
The reverberant speech degrades the speech recognition performance in the field of distant-talking speech. As one of app... [more] EA2014-78 SIP2014-119 SP2014-141
pp.37-42
HCS 2015-01-30
17:00
Kagawa Bay Resort Hotel Shodoshima (Shodoshima, Kagaewa Pref.) [Poster Presentation] Towards a Model that Represents Relationship Between Speech Parameters and Speakers' Emotional Impressions -- Improvement of Conveyed Impressions by Controlling Speech Rate and Voice Pitch --
Takahiro Ono, Hiroto Saito, Hiroshi Kaneko, Naoki Mukawa (Tokyo Denki Univ.) HCS2014-107
Speech-rate conversion (SRC) which slows speakers' utterances improves speech intelligibility.At the same time, converte... [more] HCS2014-107
pp.193-198
HCGSYMPO
(2nd)
2014-12-17
- 2014-12-19
Yamaguchi Kaikyo Messe Shimonoseki Development of a wearable device for supporting verbal communication base on the prosody
Yutaro Kajiwara (Univ. of Tsukuba), Kenji Suzuki (Univ. of Tsukuba/JST)
This study proposes a wearable device for supporting verbal communication based on the description of prosody. Verbal co... [more]
 Results 21 - 40 of 106 [Previous]  /  [Next]  
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