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Statistical Language and Speech Processing: 9th International Conference, SLSP 2021, Virtual Event, November 22-26, 2021, Proceedings 1st ed. 2021 [Pehme köide]

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  • Formaat: Paperback / softback, 111 pages, kõrgus x laius: 235x155 mm, kaal: 203 g, 22 Illustrations, color; 9 Illustrations, black and white; IX, 111 p. 31 illus., 22 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Artificial Intelligence 13062
  • Ilmumisaeg: 17-Oct-2021
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030895785
  • ISBN-13: 9783030895785
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Statistical Language and Speech Processing: 9th International Conference, SLSP 2021, Virtual Event, November 22-26, 2021, Proceedings 1st ed. 2021Suurem pilt
  • Formaat: Paperback / softback, 111 pages, kõrgus x laius: 235x155 mm, kaal: 203 g, 22 Illustrations, color; 9 Illustrations, black and white; IX, 111 p. 31 illus., 22 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Artificial Intelligence 13062
  • Ilmumisaeg: 17-Oct-2021
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030895785
  • ISBN-13: 9783030895785
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030895785.html
Märksõnad:
This book constitutes the proceedings of the 9th International Conference on Statistical Language and Speech Processing, SLSP 2021, held in Cardiff, UK, in November 2021.

The 9 full papers presented in this volume were carefully reviewed and selected from 21 submissions. The papers present topics of either theoretical or applied interest discussing the employment of statistical models (including machine learning) within language and speech processing.

Language.- Improving German Image Captions using Machine Translation
and
Transfer Learning.- Automatic News Article Generation from Legislative
Proceedings: A Phenom-based Approach.- Comparison of Czech Transformers on
Text Classification Tasks.- Constructing Sentiment Lexicon with Game for
Annotation Collection.- Robustness of Named Entity Recognition: Case of
Latvian.- Speech.- Use of Speaker Metadata for Improving Automatic
Pronunciation Assessment.- Augmenting ASR for user-generated videos with
semi-supervised training and acoustic model adaptation for Spoken Content
Retrieval.- Various DNN-HMM Architectures Used in Acoustic Modeling with
Single-Speaker and Single-Channel Invariant Representation Learning for
Robust Far-Field Speaker Recognition.