Zobrazeno 1 - 10
of 222
pro vyhledávání: '"Masashi Unoki"'
Autor:
Anuwat Chaiwongyen, Suradej Duangpummet, Jessada Karnjana, Waree Kongprawechnon, Masashi Unoki
Publikováno v:
IEEE Access, Vol 12, Pp 121958-121970 (2024)
There is a great concern regarding the misuse of deepfake speech technology to synthesize a real person’s voice. Therefore, developing speech-security systems capable of detecting deepfake speech remains paramount in safeguarding against such misus
Externí odkaz:
https://doaj.org/article/1e8c0e4c17cd40d796958453ad399b57
Publikováno v:
IEEE Access, Vol 11, Pp 84689-84698 (2023)
Fake audio detection (FAD) aims to identify fraudulent speech generated through advanced speech-synthesis techniques. Most current FAD methods rely solely on a deep neural network (DNN) framework with either speech waveforms or commonly used acoustic
Externí odkaz:
https://doaj.org/article/5fbbd8ddd4724a6b93b544bfe2ffd3ca
Publikováno v:
IEEE Access, Vol 11, Pp 141573-141584 (2023)
In speech enhancement, accurate phase reconstruction can significantly improve speech quality. While phase-aware speech enhancement methods using the complex ideal ratio mask (cIRM) have shown promise, the estimation difficulty of the phase is shared
Externí odkaz:
https://doaj.org/article/eaaa6b59af1947aa8efd515f9e552272
Publikováno v:
IEEE Access, Vol 11, Pp 106620-106649 (2023)
Deep learning can be used for audio signal classification in a variety of ways. It can be used to detect and classify various types of audio signals such as speech, music, and environmental sounds. Deep learning models are able to learn complex patte
Externí odkaz:
https://doaj.org/article/7991b4deb4004596a3e463f9af1e762d
Autor:
Yasuji Ota, Masashi Unoki
Publikováno v:
IEEE Access, Vol 11, Pp 70884-70897 (2023)
This paper proposes an anomalous sound detection (ASD) method that uses a combination of timbral metrics and short-term features tailored to industrial machine faults to identify whether the sound emitted from a target machine is anomalous. The timbr
Externí odkaz:
https://doaj.org/article/2cf6c4a44e184390923a180237e09dc4
Publikováno v:
IEEE Access, Vol 11, Pp 49431-49444 (2023)
The speech transmission index (STI) and room acoustic parameters (RAPs) are essential metrics for assessing speech quality and predicting listening difficulty in a sound field. Although STI and important RAPs, such as reverberation time and clarity,
Externí odkaz:
https://doaj.org/article/0f1e2a9285944a169c742d6c6cf1e7fa
Publikováno v:
Frontiers in Computational Neuroscience, Vol 16 (2022)
In recent years, electroencephalograph (EEG) studies on speech comprehension have been extended from a controlled paradigm to a natural paradigm. Under the hypothesis that the brain can be approximated as a linear time-invariant system, the neural re
Externí odkaz:
https://doaj.org/article/43f17a02f42647a2bdc30bebc471166c
Publikováno v:
Applied Sciences, Vol 13, Iss 10, p 6239 (2023)
We previously investigated the perception of noise-vocoded speech to determine whether the temporal amplitude envelope (TAE) of speech plays an important role in the perception of linguistic information as well as non-linguistic information. However,
Externí odkaz:
https://doaj.org/article/f69c317018dd4a3c9656344d884ed1ca
Autor:
Dung Kim Tran, Masashi Unoki
Publikováno v:
IEEE Access, Vol 9, Pp 167084-167095 (2021)
Previous studies have revealed that by mimicking the neural activity patterns of the auditory periphery to obtain perceptual features of speech signals, the resultant auditory representation is beneficial to speech-coding and pattern-analysis applica
Externí odkaz:
https://doaj.org/article/34c1182769c44d55930afc1c77b44b71
Publikováno v:
IEEE Access, Vol 8, Pp 16560-16572 (2020)
Emotion information from speech can effectively help robots understand speaker's intentions in natural human-robot interaction. The human auditory system can easily track temporal dynamics of emotion by perceiving the intensity and fundamental freque
Externí odkaz:
https://doaj.org/article/0f13d0eb0e6849aabbd453feb2e6de0f