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Obvie: interface web pour la fouille et la comparaison de textes
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In: Atelier DigitAl Humanities and cuLtural herItAge: data and knowledge management and analysis durant la conférence francophone sur l'Extraction et la Gestion des Connaissances (egc2022) ; https://hal.archives-ouvertes.fr/hal-03543362 ; Atelier DigitAl Humanities and cuLtural herItAge: data and knowledge management and analysis durant la conférence francophone sur l'Extraction et la Gestion des Connaissances (egc2022), Jan 2022, Blois, France ; https://egc2022.univ-tours.fr/ateliers/ (2022)
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Assessing the impact of OCR noise on multilingual event detection over digitised documents
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In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022)
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Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
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In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)
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In: ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora ; https://hal.archives-ouvertes.fr/hal-03623351 ; ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora, Jun 2022, Marseille, France ; https://www.clarin.eu/ParlaCLARIN-III (2022)
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A comparative study of several parameterizations for speaker recognition ...
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Speaker verification in mismatch training and testing conditions ...
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A New Amharic Speech Emotion Dataset and Classification Benchmark ...
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LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects ...
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Automatic Dialect Density Estimation for African American English ...
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Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
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Learning and controlling the source-filter representation of speech with a variational autoencoder ...
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Correcting Misproducted Speech using Spectrogram Inpainting ...
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Decoding Neural Correlation of Language-Specific Imagined Speech using EEG Signals ...
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Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation ...
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Can Social Robots Effectively Elicit Curiosity in STEM Topics from K-1 Students During Oral Assessments? ...
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Expression-preserving face frontalization improves visually assisted speech processing ...
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Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognition ...
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Multi Antenna Radar System for American Sign Language (ASL) Recognition Using Deep Learning ...
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Abstract:
This paper investigates RF-based system for automatic American Sign Language (ASL) recognition. We consider radar for ASL by joint spatio-temporal preprocessing of radar returns using time frequency (TF) analysis and high-resolution receive beamforming. The additional degrees of freedom offered by joint temporal and spatial processing using a multiple antenna sensor can help to recognize ASL conversation between two or more individuals. This is performed by applying beamforming to collect spatial images in an attempt to resolve individuals communicating at the same time through hand and arm movements. The spatio-temporal images are fused and classified by a convolutional neural network (CNN) which is capable of discerning signs performed by different individuals even when the beamformer is unable to separate the respective signs completely. The focus group comprises individuals with varying expertise with sign language, and real time measurements at 77 GHz frequency are performed using Texas Instruments (TI) ... : arXiv admin note: substantial text overlap with arXiv:2104.00217 ...
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Keyword:
FOS Electrical engineering, electronic engineering, information engineering; Signal Processing eess.SP
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URL: https://arxiv.org/abs/2203.16624 https://dx.doi.org/10.48550/arxiv.2203.16624
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