Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Zhaocheng Huang"'
Publikováno v:
IEEE Transactions on Affective Computing. 13:666-679
The massive and growing burden imposed on modern society by depression has motivated investigations into early detection through automated, scalable and non-invasive methods, including those based on speech. However, speech-based methods that capture
Publikováno v:
Journal of Healthcare Informatics Research
Currently, there is an increasing global need for COVID-19 screening to help reduce the rate of infection and at-risk patient workload at hospitals. Smartphone-based screening for COVID-19 along with other respiratory illnesses offers excellent poten
Autor:
Zhaocheng Huang, Julien Epps
Publikováno v:
IEEE Transactions on Affective Computing. 11:653-668
Phonetic variability has long been considered a confounding factor for emotional speech processing, so phonetic features have been rarely explored. However, surprisingly some features with purely phonetic information have shown state-of-the-art perfo
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2021
While the psychological Stroop color test has frequently been used to analyze response delays in temporal cognitive processing, minimal research has examined incorrect/correct verbal test response pattern differences exhibited in healthy control and
Autor:
Zhaocheng Huang, Lei Liu, Lanyao Qin, Yonglin Huang, Sha Lan, Yi Xiang, Xiaopeng Xie, Changjin Guo
Publikováno v:
2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys).
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 14:435-448
The processing of speech as an explicit sequence of events is common in automatic speech recognition (linguistic events), but has received relatively little attention in paralinguistic speech classification despite its potential for characterizing br
Generic pre-trained speech and text representations promise to reduce the need for large labeled datasets on specific speech and language tasks. However, it is not clear how to effectively adapt these representations for speech emotion recognition. R
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da3158a6c479902eb690a4d94ba6ba53
http://arxiv.org/abs/2112.00158
http://arxiv.org/abs/2112.00158
Autor:
Liang Lei, Lanyao Qin, Zhaocheng Huang, Huiming Liang, Yunfeng Jiang, Yuanyuan He, Yanwei Yin
Publikováno v:
2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT).
Publikováno v:
2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT).
Publikováno v:
ICASSP
Detecting depression from the voice in naturalistic environments is challenging, particularly for short-duration audio recordings. This enhances the need to interpret and make optimal use of elicited speech. The rapid consonant-vowel syllable combina