Statistical Language and Speech Processing
9th International Conference, SLSP 2021, Virtual Event, November 22-26, 2021, Proceedings
Published on 17. October 2021
Book
Paperback/Softback
IX, 111 pages
978-3-030-89578-5 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
9 s/w Abbildungen, 22 farbige Abbildungen
IX, 111 p. 31 illus., 22 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 8 mm
Weight
201 gr
ISBN-13
978-3-030-89578-5 (9783030895785)
DOI
10.1007/978-3-030-89579-2
Schweitzer Classification
Other editions
Additional editions
Luis Espinosa-Anke | Carlos Martín-Vide | Irena Spasic
Statistical Language and Speech Processing
9th International Conference, SLSP 2021, Virtual Event, November 22-26, 2021, Proceedings
E-Book
10/2021
Springer
€58.84
Available for download
Content
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.
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.