Statistical Language and Speech Processing
8th International Conference, SLSP 2020, Cardiff, UK, October 14-16, 2020, Proceedings
Published on 25. September 2020
X, 183 pages
978-3-030-59430-5 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
X, 183 p. 68 illus., 36 illus. in color.
ISBN-13
978-3-030-59430-5 (9783030594305)
DOI
10.1007/978-3-030-59430-5
Schweitzer Classification
Other editions
Additional editions
Luis Espinosa-Anke | Carlos Martín-Vide | Irena Spasic
Statistical Language and Speech Processing
8th International Conference, SLSP 2020, Cardiff, UK, October 14-16, 2020, Proceedings
Book
09/2020
Springer
€53.49
Shipment within 7-9 days
Content
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.
