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1
Perception and Representation of Lexical Tones in Native Mandarin-Learning Infants and Toddlers
Shi, Rushen; Gao, Jun; Achim, André. - : Frontiers Media S.A., 2017
BASE
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2
Encoding and Decoding of Emotional Speech : A Cross-Cultural and Multimodal Study between Chinese and Japanese
Li, Aijun. - Berlin : Springer Berlin, 2016
DNB Subject Category Language
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3
Encoding and Decoding of Emotional Speech : A Cross-Cultural and Multimodal Study between Chinese and Japanese
Li, Aijun [Verfasser]. - Berlin, Heidelberg : Springer Berlin Heidelberg, 2015
DNB Subject Category Language
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4
Encoding and decoding of emotional speech : a cross-cultural and multimodal study between Chinese and Japanese
Li, Aijun [Verfasser]. - 2015
DNB Subject Category Language
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5
Encoding and decoding of emotional speech : a cross-cultural and multimodal study between Chinese and Japanese
Li, Aijun. - Heidelberg : Springer, 2015
BLLDB
UB Frankfurt Linguistik
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6
Interconnected growing self-organizing maps for auditory and semantic acquisition modeling
Abstract: Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic–semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory–semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.
Keyword: Psychology
URL: http://www.ncbi.nlm.nih.gov/pubmed/24688478
https://doi.org/10.3389/fpsyg.2014.00236
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3960950
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7
Prosody conversion from neutral speech to emotional speech
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 14 (2006) 4, 1145-1154
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8
A Learner Corpus- ESCCL*
In: http://www.isca-speech.org/archive/sp2008/papers/sp08_155.pdf
BASE
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9
Perception and Production of Prominence Distribution Patterns of Chinese EFL Learners
In: http://speechprosody2010.illinois.edu/papers/100046.pdf
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