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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 11:30 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Implementation of a Lightweight Automatic Speech Recognition System at the Edge Haotian Tan, Junichi Akita (Kanazawa Univ.) |
Automatic speech recognition (ASR) on the cloud has been widely adopted and has demonstrated satisfactory performance. W... [more] | |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 12:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Incorporating Acoustic and Textual Information for Language Modeling in Code-switching Speech Recognition Roland Hartanto, Kuniaki Uto, Koichi Shinoda (TokyoTech)  EA2021-73 SIP2021-100 SP2021-58 |
People who speak two or more languages tend to alternate the language when they are speaking. This particular phenomenon... [more] | EA2021-73 SIP2021-100 SP2021-58 pp.56-63 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2021-12-02 15:20 |
Online | Online | improvement of multilingual speech emotion recognition by normalizing features using CRNN Jinhai Qi, Motoyuki Suzuki (OIT) NLC2021-22 SP2021-43 |
In this research, a new multilingual emotion recognition method by normalizing features using CRNN has been proposed. We... [more] | NLC2021-22 SP2021-43 pp.22-26 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-18 15:00 |
Online | Online | Protection method with audio processing against Audio Adversarial Example Taisei Yamamoto, Yuya Tarutani, Yukinobu Fukusima, Tokumi Yokohira (Okayama Univ) SP2021-4 |
Machine learning technology has improved the recognition accuracy of voice recognition, and demand for voice recognition... [more] | SP2021-4 pp.19-24 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-19 09:30 |
Online | Online | [Invited Talk]
Toward a Unification of Various Speech Processing Tasks Based on End-to-End Neural networks Shinji Watanabe (CMU) SP2021-8 |
This presentation will introduce the recent progress of speech processing technologies based on end-to-end neural networ... [more] | SP2021-8 p.38 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-19 13:00 |
Online | Online | A Study on Error Correction for Improving the Accuracy of Acoustic Models Saki Anazawa, Naofumi Aoki, Yoshinori Dobashi (Hokkaido Univ.) SP2021-12 |
People with ALS (amyotrophic lateral sclerosis) or dysarthria sometimes use their own voice for speech synthesis. In thi... [more] | SP2021-12 pp.51-52 |
| NS | 2021-04-15 14:25 |
Online | Online | [Invited Talk]
Speech recognition research moving forward with the development of deep learning technology Hiromitsu Nishizaki (Univ. of Yamanashi) NS2021-7 |
In recent years, deep learning technology has been developing rapidly. Along with the development of deep learning, auto... [more] | NS2021-7 pp.37-42 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 17:10 |
Online | Online | An investigation of rhythm-based speaker embeddings for phoneme duration modeling Kenichi Fujita, Atsushi Ando, Yusuke Ijima (NTT) EA2020-77 SIP2020-108 SP2020-42 |
In this study, we propose a speaker embedding method suitable for modeling phoneme duration length for each individual i... [more] | EA2020-77 SIP2020-108 SP2020-42 pp.103-108 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 17:35 |
Online | Online | [Short Paper]
Comparison of End-to-End Models for Joint Speaker and Speech Recognition Kak Soky (Kyoto Univ.), Sheng Li (NICT), Masato Mimura, Chenhui Chu, Tatsuya Kawahara (Kyoto Univ.) EA2020-78 SIP2020-109 SP2020-43 |
In this paper, we investigate the effectiveness of using speaker information on the performance of speaker-imbalanced au... [more] | EA2020-78 SIP2020-109 SP2020-43 pp.109-113 |
| MVE, IPSJ-CVIM | 2021-01-21 15:50 |
Online | Online | Customer service training VR system with spoken voice traning Toki Nishio, Soichiro Iida (Univ. of Tsukuba), Yuta Sano, Leow Chee Siang, Hiromitsu Nishizaki (Univ. of Yamanashi), Takehito Utsuro, Junichi Hoshino (Univ. of Tsukuba) MVE2020-32 |
A filler is a word that has no meaning in itself and is used to fill gaps in conversation. In customer service, this fil... [more] | MVE2020-32 pp.13-16 |
| CQ, CBE (Joint) |
2021-01-22 14:00 |
Online | Online | [Invited Lecture]
A Study on Correlation between Automatic Speech Recognition Accuracy and Speech QoE Masashi Yamashita, Hiroshi Matsunaga, Toyota Nishi (DOCOMO Technology) CQ2020-99 |
In recent years, as the quality of mobile networks has improved, it has become more critical to maintain and improve the... [more] | CQ2020-99 pp.145-148 |
| EA | 2020-12-14 10:05 |
Online | Online | Speech Signal Detection Based on Bayesian Estimation by Observing Air-Conducted Speech under Existence of Surrounding Noise with Aid of Bone-Conducted Speech Akira Ikuta, Hisako Orimoto (Prefectural Univ. of Hiroshima), Kouji Hasegawa (Hiroshima Prefectural Technology Research Inst.) EA2020-48 |
When applying speech recognition systems to actual circumstances such as inspection and maintenance operations in indust... [more] | EA2020-48 pp.13-18 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2020-12-02 09:40 |
Online | Online | Fast End-to-End Speech Recognition with CTC and Mask Predict Yosuke Higuchi (Waseda Univ.), Hirofumi Inaguma (Kyoto Univ.), Shinji Watanabe (JHU), Tetsuji Ogawa, Tetsunori Kobayashi (Waseda Univ.) NLC2020-13 SP2020-16 |
We present a fast non-autoregressive (NAR) end-to-end automatic speech recognition (E2E-ASR) framework, which generates ... [more] | NLC2020-13 SP2020-16 pp.1-6 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2020-12-02 13:50 |
Online | Online | Multi-Modal Emotion Recognition by Integrating of Acoustic and Linguistic Features Ryotaro Nagase, Takahiro Fukumori, Yoichi Yamashita (Ritsumeikan Univ.) NLC2020-14 SP2020-17 |
In recent years, the advanced techique of deep learning has improved the performance of Speech Emotional Recognition as ... [more] | NLC2020-14 SP2020-17 pp.7-12 |
| SIS, IPSJ-AVM, ITE-3DMT [detail] | 2020-06-04 14:00 |
Online | Online | An experimental comparison of CNN- and CRNN-CTC for automatic phrase speech recognition systems using a children's speech database Yunzhe Wang, Yu Tian (Hokkaido Univ.), Yoshikazu Miyanaga (CIST), Hiroshi Tsutsui (Hokkaido Univ.) SIS2020-9 |
Children's speech recognition is still a challenging issue. In the case of children's speeches, the accuracy of conventi... [more] | SIS2020-9 pp.49-54 |
| SC | 2020-03-16 10:30 |
Online | Online | Cloud Speech Recognition Process Management Method Based on Device Sensor Information Yu Fujita, Isao Tazawa, Masaharu Ukeda (Hitachi) SC2019-38 |
In recent years, the use of voice User Interface (VUI) to make the service interactive using speech is widespread. When ... [more] | SC2019-38 pp.23-28 |
| ET | 2020-03-07 10:35 |
Kagawa | National Institute of Technology, Kagawa Collage (Cancelled but technical report was issued) |
Implementation and evaluation of language learning support module applying speech recognition Yusuke Kawamura, Chunxiang Chen, Renfeng Hou (PUH) ET2019-87 |
The development of speech recognition and speech synthesis technology has been remarkable due to the development of deep... [more] | ET2019-87 pp.63-67 |
| SP, EA, SIP | 2020-03-02 13:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Data augmentation for ASR system by using locally time-reversed speech
-- Temporal inversion of feature sequence -- Takanori Ashihara, Tomohiro Tanaka, Takafumi Moriya, Ryo Masumura, Yusuke Shinohara, Makio Kashino (NTT) EA2019-110 SIP2019-112 SP2019-59 |
Data augmentation is one of the techniques to mitigate overfitting and improve robustness against several acoustic varia... [more] | EA2019-110 SIP2019-112 SP2019-59 pp.53-58 |
| SP, EA, SIP | 2020-03-02 15:45 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Performance evaluation of distilling knowledge using encoder-decoder for CTC-based automatic speech recognition systems Takafumi Moriya, Hiroshi Sato, Tomohiro Tanaka, Takanori Ashihara, Ryo Masumura, Yusuke Shinohara (NTT) EA2019-131 SIP2019-133 SP2019-80 |
We present a novel training approach for connectionist temporal classification (CTC) -based automatic speech recognition... [more] | EA2019-131 SIP2019-133 SP2019-80 pp.175-180 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
[Poster Presentation]
Implementation of a high-accuracy method for automatic fluency scoring of spontaneous English utterances by Japanese learners Ayano Yasukagawa, Shintaro Ando, Eisuke Konno, Zhenchao Lin, Yusuke Inoue, Daisuke Saito, Nobuaki Minematsu (UTokyo), Kazuya Saito (UCL) EA2019-134 SIP2019-136 SP2019-83 |
These days, many teachers claim importance of not native-likeness-based but intelligibility-based assessment of pronunci... [more] | EA2019-134 SIP2019-136 SP2019-83 pp.189-194 |
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