Research & Development

Publications (JP/EN)


D. Hossain and Y. Sato, "Efficient Corpus Design for Wake-Word Detection," 2021 IEEE Spoken Language Technology Workshop (SLT), 2021


C. Liu and Y. Sato, "Self-Attention for Multi-Channel Speech Separation in Noisy and Reverberant Environments," 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2020.


Z. Zhu and Y. Sato, "Reconciliation of Multiple Corpora for Speech Emotion Recognition by Multiple Classifiers with an Adversarial Corpus Discriminator," in Proceedings of the 21st Annual Conference of the International Speech Communication Association (Interspeech), 2020, pp. 2342-2346.


Y. Sato and K. Miyazawa,"Quality estimation for partially subjective classification tasks via crowdsourcing," in Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC), 2020, pp. 229–235.


K.Miyazawa,"Utilization of ELAN in communication studies: Annotating audio and video data," Acoustic Society of Japan(ASJ), Vol. 75, No. 6, pp. 344-350, 2019.


N. Ikeda, Y. Sato and H. Takahashi,"Short utterance speaker recognition by reservoir with self-organized mapping," 2018 IEEE Spoken Language Technology Workshop (SLT), Athens, Greek, 2018, pp. 1073-1077.


Y. Hayashibe, Information Processing Society of Japan (IPSJ) SIG Technical Reports, Vol. 2017-NL-231, No. 9, pp. 1-8, 2017.

Y. Sato,"Application and Prospect of Spoken Language Technology at Fairy Devices," Information Processing Society of Japan (IPSJ) SIG Technical Reports, Vol. 2017-SLP-118, No.6, pp. 1-2, 2017.

Fairy Blog Articles (EN)

THINKLET®️ ; connected worker solution as a bridge between humans, AI & machines

2020-06-26 13:14

Developed for the digital transformation of field operations. The connected worker solution "THINKLET" provides field workers with a physical and operational burden and It digitizes operations without the burden of change, connects humans and AI, and enables collaboration with machines.