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Y. H. Cheng

dblp:45/8416 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none

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

Artificial intelligence and machine learning · 1Theory of computation · 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%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Speech recognition and synthesis › automatic speech recognition
tone recognition		 0.011995
Tone recognition of isolated Cantonese syllables · IEEE Trans. Speech Audio Process. 1995

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

suprasegmental feature extraction · 0.0feedforward neural network · 0.0
YearPublicationVenuePosition
2005 Global Stability Results for the Weak Vector Variational Inequality
Y. H. Cheng, D. L. Zhu
 J. Glob. Optim.1
1995 Tone recognition of isolated Cantonese syllables
abstract
Tone identification is essential for the recognition of the Chinese language, specifically far Cantonese which is well known for being very rich in tones. The paper presents an efficient method for tone recognition of isolated Cantonese syllables. Suprasegmental feature parameters are extracted from the voiced portion of a monosyllabic utterance and a three-layer feedforward neural network is used to classify these feature vectors. Using a phonologically complete vocabulary of 234 distinct syllables, the recognition accuracy for single-speaker and multispeaker is given by 89.0% and 87.6% respectively.>
Tan Lee, Pak-Chung Ching, Lai-Wan Chan, Y. H. Cheng, Brian Kan-Wing Mak
 IEEE Trans. Speech Audio Process.4