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Statistical Language and Speech Processing: 8th International Conference, SLSP 2020, Cardiff, UK, October 14–16, 2020, Proceedings de Luis Espinosa-Anke

Statistical Language and Speech Processing: 8th International Conference, SLSP 2020, Cardiff, UK, October 14–16, 2020, Proceedings: Lecture Notes in Computer Science, cartea 12379

Editat de Luis Espinosa-Anke, Carlos Martín-Vide, Irena Spasić
en Limba Engleză Paperback – 26 sep 2020
This book constitutes the proceedings of the 8th International Conference on Statistical Language and Speech Processing, SLSP 2020, held in Cardiff, UK, in October 2020.
The 13 full papers presented together with one invited paper in this volume were carefully reviewed and selected from 25 submissions. They papers cover the wide spectrum of statistical methods that are currently in use in computational language or speech processing.
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Specificații

ISBN-13: 9783030594299
ISBN-10: 3030594297
Pagini: 183
Ilustrații: X, 183 p. 68 illus., 36 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.28 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Grapheme-to-Phoneme Transduction for Cross-Language ASR.- Language Processing.-Conditioned Text Generation with Transfer for Closed-Domain Dialogue Systems.- FacTweet: Profiling Fake News Twitter Accounts.- Named Entity Recognition for Icelandic: Annotated Corpus and Models.- BERT-based Sentiment Analysis using Distillation.- A Cognitive Approach to Parsing with Neural Networks.- S-capade: Spelling Correction Aimed at Particularly Deviant Errors.- Exploring Parameter Sharing Techniques for Cross-Lingual and Cross-Task Supervision.- A Discourse-Informed Approach for Cost-E ective Extractive Summarization.- Towards eXplainable AI in Text Features Engineering for Concept Recognition.- A Comparison of Metric Learning Loss Functions for End-To-End Speaker Verification.- ANN-MLP Classifier of Native and Nonnative Speakers Using Speech Rhythm Cues.- Deep Variational Metric Learning for Transfer of Expressivity in Multispeaker Text to Speech.- Generative Adversarial Network-based Semi-Supervised Learning for Pathological Speech Classfication.