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Extending the Cascaded Gaussian Mixture Regression Framework for Cross-Speaker Acoustic-Articulatory Mapping
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In: ISSN: 2329-9290 ; EISSN: 2329-9304 ; IEEE/ACM Transactions on Audio, Speech and Language Processing ; https://hal.archives-ouvertes.fr/hal-01485540 ; IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (3), pp.662-673. ⟨10.1109/TASLP.2017.2651398⟩ (2017)
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L'INVERSION LOCATIVE REVISITÉE : À PROPOS DE LA NOTION DE « DÉCLENCHEUR »
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In: ISSN: 0182-5887 ; Verbum (Presses Universitaires de Nancy) ; https://hal.archives-ouvertes.fr/hal-01699439 ; Verbum (Presses Universitaires de Nancy), Université de Nancy II, 2017 (2017)
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A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion
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In: Interspeech 2017 ; https://hal.archives-ouvertes.fr/hal-02166128 ; Interspeech 2017, Aug 2017, Stockholm, Sweden. pp.984-988, ⟨10.21437/Interspeech.2017-804⟩ (2017)
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Abstract:
International audience ; We address the speaker-independent acoustic inversion (AI) problem, also referred to as acoustic-to-articulatory mapping. The scarce availability of multi-speaker articulatory data makes it difficult to learn a mapping which generalizes from a limited number of training speakers and reliably reconstructs the artic-ulatory movements of unseen speakers. In this paper, we propose a Multi-task Learning (MTL)-based approach that explicitly separates the modeling of each training speaker AI peculiarities from the modeling of AI characteristics that are shared by all speakers. Our approach stems from the well known Reg-ularized MTL approach and extends it to feed-forward deep neural networks (DNNs). Given multiple training speakers, we learn for each an acoustic-to-articulatory mapping represented by a DNN. Then, through an iterative procedure, we search for a canonical speaker-independent DNN that is "sim-ilar" to all speaker-dependent DNNs. The degree of similarity is controlled by a regularization parameter. We report experiments on the University of Wisconsin X-ray Microbeam Database under different training/testing experimental settings. The results obtained indicate that our MTL-trained canonical DNN largely outperforms a standardly trained (i.e., single task learning-based) speaker independent DNN.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; [SCCO]Cognitive science; acoustic-to-articulatory map- ping; Index Terms: acoustic inversion; multi-task learning; XRMB
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URL: https://doi.org/10.21437/Interspeech.2017-804
https://hal.archives-ouvertes.fr/hal-02166128
https://hal.archives-ouvertes.fr/hal-02166128/file/0804.pdf
https://hal.archives-ouvertes.fr/hal-02166128/document
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Será a interface sintaxe-discurso necessariamente um locus de opcionalidade em L2? ; O caso da inversão locativa em inglês L2
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Is the syntax-discourse interface a locus of permanent optionality? ; The case of locative inversion in L2 English
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Articulatory representations to address acoustic variability in speech ...
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ЯЗЫКОВАЯ ЭКСПРЕССИЯ В СОВРЕМЕННОЙ ПОЭЗИИ (НА ПРИМЕРЕ ПОЭЗИИ J.SILVER) ... : LANGUAGE EXPRESSIVENESS IN MODERN POETRY (ON THE EXAMPLE OF J.SILVER'S POETRY) ...
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Transcranial Direct Current Stimulation (tDCS) and the Face Inversion Effect: Anodal stimulation at Fp3 reduces recognition for upright faces
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Articulatory representations to address acoustic variability in speech
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| 10 |
The Syntax of the Abstract-type Measurement Construction in Mandarin Chinese
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In: Studies in Chinese Linguistics, Vol 38, Iss 1, Pp 35-61 (2017) (2017)
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What the giant tells us about agreeing post-verbal subjects in Xhosa
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In: Stellenbosch Papers in Linguistics Plus, Vol 52, Iss 0, Pp 73-100 (2017) (2017)
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The emergence of Brazilian Portuguese: Earlier evidence for the development of a partial null subject grammar
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In: Proceedings of the Linguistic Society of America; Vol 2 (2017): Proceedings of the Linguistic Society of America; 31:1–15 ; 2473-8689 (2017)
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