• Refine your search:
  • 
    Keyword:
    
    • Audio and Speech Processing eess.AS (3)
    • Computation and Language cs.CL (3)
    • FOS Computer and information sciences (3)
    • FOS Electrical engineering, electronic engineering, information engineering (3)
    • Sound cs.SD (3)
  • 
    Creator / Publisher
  • 
    Year
  • 
    Medium:
    
    • Online (3)
  • 
    Type:
    
    • Article (2)
    • Miscellaneous (1)
  • 
    BLLDB-Access

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation ... Georges, Marc-Antoine; Diard, Julien; Girin, Laurent. - : arXiv, 2022 BASE Show details 2 Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding ... Sankar, Sanjana; Beautemps, Denis; Hueber, Thomas. - : arXiv, 2022 Abstract: This paper proposes a simple and effective approach for automatic recognition of Cued Speech (CS), a visual communication tool that helps people with hearing impairment to understand spoken language with the help of hand gestures that can uniquely identify the uttered phonemes in complement to lipreading. The proposed approach is based on a pre-trained hand and lips tracker used for visual feature extraction and a phonetic decoder based on a multistream recurrent neural network trained with connectionist temporal classification loss and combined with a pronunciation lexicon. The proposed system is evaluated on an updated version of the French CS dataset CSF18 for which the phonetic transcription has been manually checked and corrected. With a decoding accuracy at the phonetic level of 70.88%, the proposed system outperforms our previous CNN-HMM decoder and competes with more complex baselines. ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://arxiv.org/abs/2204.04965 https://dx.doi.org/10.48550/arxiv.2204.04965 BASE Hide details 3 Learning robust speech representation with an articulatory-regularized variational autoencoder ... Georges, Marc-Antoine; Girin, Laurent; Schwartz, Jean-Luc. - : arXiv, 2021 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 3 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0