Speech and computer : 22nd International Conference, SPECOM 2020, St. Petersburg, Russia, October 7-9, 2020, Proceedings / Alexey Karpov, Rodmonga Potapova (eds.).

This book constitutes the proceedings of the 22nd International Conference on Speech and Computer, SPECOM 2020, held in St. Petersburg, Russia, in October 2020. The 65 papers presented were carefully reviewed and selected from 160 submissions. The papers present current research in the area of compu...

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Bibliographic Details
Corporate Author: International Conference Speech and Computer Online
Other Authors: Karpov, Alexey (Editor), Potapova, Rodmonga (Editor)
Format: eBook
Language:English
Published: Cham : Springer, 2020.
Series:Lecture notes in computer science. Lecture notes in artificial intelligence.
Lecture notes in computer science ; 12335.
LNCS sublibrary. Artificial intelligence.
Subjects:
Online Access:Click for online access
Description
Summary:This book constitutes the proceedings of the 22nd International Conference on Speech and Computer, SPECOM 2020, held in St. Petersburg, Russia, in October 2020. The 65 papers presented were carefully reviewed and selected from 160 submissions. The papers present current research in the area of computer speech processing including speech science, speech technology, natural language processing, human-computer interaction, language identification, multimedia processing, human-machine interaction, deep learning for audio processing, computational paralinguistics, affective computing, speech and language resources, speech translation systems, text mining and sentiment analysis, voice assistants, etc. Due to the Corona pandemic SPECOM 2020 was held as a virtual event.
Item Description:International conference proceedings.
"Due to the Corona pandemic SPECOM 2020 was held as a virtual event."
Includes author index.
Physical Description:1 online resource (xiv, 689 pages) : illustrations (some color)
Bibliography:References-Exploration of End-to-End ASR for OpenSTT-Russian Open Speech-to-Text Dataset-1 Introduction-2 Related Work-3 End-to-End ASR Models-3.1 Connectionist Temporal Classification (CTC)-3.2 Neural Transducer-3.3 Attention-Based Models-4 OpenSTT Dataset-5 Experimental Setup-5.1 Baseline System-5.2 End-to-End Modeling-6 Results-7 Conclusion-References-Directional Clustering with Polyharmonic Phase Estimation for Enhanced Speaker Localization-1 Introduction-2 Preliminary Information-2.1 Problem Formulation.
ISBN:9783030602765
3030602761
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed December 2, 2020).