• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Nguyen, Thai-Son (4)
    • Waibel, Alex (4)
    • Stüker, Sebastian (3)
    • Ha, Thanh-Le (2)
    • Müller, Markus (2)
    • Niehues, Jan (2)
    • Sperber, Matthias (2)
    • Ansari, Ebrahim (1)
    • Bojar, Ondřej (1)
    • Canton, Chiara (1)
    •   more
  • 
    Year:
    
    • 2022 (2)
    • 2021 (1)
    • 2020 (1)
  • 
    Medium
  • 
    Type
  • 
    BLLDB-Access:
    • free (4)
    • subject to license (0)

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 – 4 of 4 1 KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning Nguyen, Thai-Son; Zenkel, Thomas; Waibel, Alex. - : Association for Computational Linguistics, 2022 BASE Show details 2 Lecture Translator Speech translation framework for simultaneous lecture translation Waibel, Alex; Nguyen, Thai-Son; Cho, Eunah. - : Association for Computational Linguistics, 2022 BASE Show details 3 ELITR Multilingual Live Subtitling: Demo and Strategy ... Bojar, Ondřej; Macháček, Dominik; Sagar, Sangeet. - : ACL Anthology, 2021 BASE Show details 4 Super-Human Performance in Online Low-latency Recognition of Conversational Speech ... Nguyen, Thai-Son; Stueker, Sebastian; Waibel, Alex. - : arXiv, 2020 Abstract: Achieving super-human performance in recognizing human speech has been a goal for several decades, as researchers have worked on increasingly challenging tasks. In the 1990's it was discovered, that conversational speech between two humans turns out to be considerably more difficult than read speech as hesitations, disfluencies, false starts and sloppy articulation complicate acoustic processing and require robust handling of acoustic, lexical and language context, jointly. Early attempts with statistical models could only reach error rates over 50% and far from human performance (WER of around 5.5%). Neural hybrid models and recent attention-based encoder-decoder models have considerably improved performance as such contexts can now be learned in an integral fashion. However, processing such contexts requires an entire utterance presentation and thus introduces unwanted delays before a recognition result can be output. In this paper, we address performance as well as latency. We present results for a system ... : To appear in Interspeech 2021 ... Keyword: Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2010.03449 https://arxiv.org/abs/2010.03449 BASE Hide 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 4 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0