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Yousheng Chen

dblp:82/10793 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Speech recognition and synthesis · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Speech recognition and synthesis › speech enhancement
beamforming
0.112012
A Normalized Beamforming Algorithm for Broadband Speech Using a Continuous Interleaved Sampling Strategy · IEEE Trans. Speech Audio Process. 2012
Natural language and speech › Speech recognition and synthesis
speech enhancement
0.112012
A Normalized Beamforming Algorithm for Broadband Speech Using a Continuous Interleaved Sampling Strategy · IEEE Trans. Speech Audio Process. 2012
Medical and health informatics › neural prosthesis
cochlear implant speech processing
0.012012
A Normalized Beamforming Algorithm for Broadband Speech Using a Continuous Interleaved Sampling Strategy · IEEE Trans. Speech Audio Process. 2012

Methods — techniques the papers use, named apart from their topics

delay beamforming · 0.3continuous interleaved sampling · 0.3
YearPublicationVenuePosition
2012 A Normalized Beamforming Algorithm for Broadband Speech Using a Continuous Interleaved Sampling Strategy
abstract
The delay beamforming method, one of the most effective microphone array techniques, requires minimal computational complexity and enjoys wide usage in narrowband signal applications. However, the method suffers from high losses of low-frequency sound and is generally not suitable for broadband signals. In this paper, a novel normalized beamforming algorithm is introduced for broadband speech applications in multichannel cochlear implant (CI), which can be adjusted based on application conditions. The proposed algorithm can, with minimal computational complexity, accurately and effectively compensate for changes in signal beam pattern, in accordance with a preselected benchmark. In addition, this method can be combined with the widely used continuous interleaved sampling (CIS) strategy, adding to its practical value.
Yousheng Chen, Qin Gong
IEEE Trans. Speech Audio Process.1