Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Chang Chun Bao"'
Publikováno v:
In New Carbon Materials February 2016 31(1):46-54
Publikováno v:
Tongxin xuebao, Vol 35, Pp 183-190 (2014)
In order to improve the performance of source localization in noisy and reverberant environments,a novel time delay estimation (TDE) method was proposed.This method is called acoustical transfer function ratio based on statistical model (ATFR-SM).In
Externí odkaz:
https://doaj.org/article/d41085d2e03940dc94a6b73b0f9af762
Publikováno v:
Tongxin xuebao, Vol 34, Pp 95-101 (2013)
A combined wideband speech enhancement method based on statistical model and empirical mode decomposition (EMD) was proposed.First,statistical model was used to eliminate the main noise component in noisy speech.Then,the residual noise was further su
Externí odkaz:
https://doaj.org/article/0b5a7aaec85147db82e1b64debad1e3f
Publikováno v:
Tongxin xuebao, Vol 34, Pp 120-130 (2013)
A bandwidth extension method based on audio classification was proposed.Time series of audio signals were classified into four types based on recurrence plot and recurrence quantification analysis,and the fine spectrums were recovered by taking advan
Externí odkaz:
https://doaj.org/article/8bd086ce47034583b1cdcd33000a2f3f
Publikováno v:
Tongxin xuebao, Vol 34, Pp 20-30 (2013)
A hiss noise reduction method used for audio signals based on AAC bit-stream in compressed domain was proposed.The input was AAC bit-stream derived from noisy audio signals,and the output was the enhanced AAC bit-stream used for decoder.First,Hiss no
Externí odkaz:
https://doaj.org/article/694de56d769340fa8ae8f452ef0b8c20
Publikováno v:
Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35f78b51fbb92c772bd5c59fea1bf2ab
https://doi.org/10.2991/icwcsn-16.2017.88
https://doi.org/10.2991/icwcsn-16.2017.88
Autor:
Chang-Chun Bao, Yong Ma
Publikováno v:
Electronics Letters. 51:651-653
Sparse deep neural networks (SDNNs) for speaker segmentation are proposed. First, the SDNNs are trained using the side information that is the class label of the input. Then, speaker-specific features are extracted from the super-vector feature of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3642c660e9af6af8e39009abeb30a0c4
https://doi.org/10.1049/el.2015.0298
https://doi.org/10.1049/el.2015.0298
Autor:
Liang Zhang, Sheng Tao Liu, Guo Fang Li, Li Dong Chen, Jun Yu Xue, Chang Chun Bao, Dong Wang, Shu Ying Ma, Yan Liu
Publikováno v:
Advanced Materials Research. :145-150
The information monitoring points for greenhouse environment were scattered, so a wireless sensor network with star-type network topology was designed and the wireless monitoring system for greenhouse was developed. By employing CC2430 chip as the co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::889733dfd2c77bf77c37cfde5ab06fed
https://doi.org/10.4028/www.scientific.net/amr.108-111.145
https://doi.org/10.4028/www.scientific.net/amr.108-111.145
Publikováno v:
The Journal of the Acoustical Society of America. 138(3)
This letter proposes an efficient parameterization of the three-dimensional room transfer function (RTF) which is robust for the position variations of source and receiver in respective horizontal planes. Based on azimuth harmonic analysis, the propo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ef03b517da7f2e4263238b5c189367b
https://pubmed.ncbi.nlm.nih.gov/26428827
https://pubmed.ncbi.nlm.nih.gov/26428827
Autor:
Rui Rui, Chang-chun Bao
Publikováno v:
SPIE Proceedings.
Audio classification is the basis of content-based audio analysis and retrieval. The conventional classification methods mainly depend on feature extraction of audio clip, which certainly increase the time requirement for classification. An approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac07d6ac1e317d6d25d555d4a1869590
https://doi.org/10.1117/12.2013917
https://doi.org/10.1117/12.2013917