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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 Effective keyword search for low-resourced conversational speech Lileikyte, Rasa; Fraga-Silva, Thiago; Lamel, Lori... In: icassp 2017 ; https://hal.archives-ouvertes.fr/hal-01744176 ; icassp 2017, IEEE, Mar 2017, La Nouvelle Orléans, United States (2017) BASE Show details 2 Language Recognition for Dialects and Closely Related Languages Gelly, Grégory; Gauvain, Jean-Luc; Lamel, Lori... In: Odyssey 2016 ; https://hal.archives-ouvertes.fr/hal-01744188 ; Odyssey 2016, Jun 2016, Bilbao, Spain (2016) BASE Show details 3 Investigating techniques for low resource conversational speech recognition Laurent, Antoine; Fraga-Silva, Thiago; Lamel, Lori; Gauvain, Jean-Luc In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01515254 ; 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Mar 2016, Shangai, China. pp.5975-5979, ⟨10.1109/ICASSP.2016.7472824⟩ ; www.icassp2016.org (2016) Abstract: International audience ; In this paper we investigate various techniques in order to build effective speech to text (STT) and keyword search (KWS) systems for low resource conversational speech. Sub-word decoding and graphemic mappings were assessed in order to detect out-of-vocabulary keywords. To deal with the limited amount of transcribed data, semi-supervised training and data selection methods were investigated. Robust acoustic features produced via data augmentation were evaluated for acoustic modeling. For language modeling, automatically retrieved conversational-like Webdata was used, as well as neural network based models. We report STT improvements with all the techniques, but interestingly only some improve KWS performance. Results are reported for the Swahili language in the context of the 2015 OpenKWS Evaluation. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; conversational speech; keyword spotting; low-ressource languages; Speech recognition URL: https://hal-univ-lemans.archives-ouvertes.fr/hal-01515254/file/Laurent16.pdf https://hal-univ-lemans.archives-ouvertes.fr/hal-01515254/document https://doi.org/10.1109/ICASSP.2016.7472824 https://hal-univ-lemans.archives-ouvertes.fr/hal-01515254 BASE Hide details

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