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Deep Learning Based Speech Quality Prediction (Record no. 200458485)

MARC details
000 -LEADER
fixed length control field	03209nam a22005895i 4500
003 - CONTROL NUMBER IDENTIFIER
control field	TR-AnTOB
005 - DATE AND TIME OF LATEST TRANSACTION
control field	20231116090901.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field	cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	220224s2022 sz \| s \|\|\|\| 0\|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9783030914790
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code	10.1007/978-3-030-91479-0
Source of number or code	doi
040 ## - CATALOGING SOURCE
Original cataloging agency	TR-AnTOB
Language of cataloging	eng
Description conventions	rda
Transcribing agency	TR-AnTOB
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title	İngilizce
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number	Q325.73
072 #7 - SUBJECT CATEGORY CODE
Subject category code	TJF
Source	bicssc

Subject category code	UYS
Source	bicssc

Subject category code	TEC008000
Source	bisacsh

Subject category code	TJF
Source	thema

Subject category code	UYS
Source	thema
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR)	Q325.73EBK
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name	Mittag, Gabriel.
Relator term	author.
Relator code	aut
--	http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title	Deep Learning Based Speech Quality Prediction
Medium	[electronic resource] /
Statement of responsibility, etc.	by Gabriel Mittag.
250 ## - EDITION STATEMENT
Edition statement	1st ed. 2022.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture	Cham :
Name of producer, publisher, distributor, manufacturer	Springer International Publishing :
--	Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice	2022.
300 ## - PHYSICAL DESCRIPTION
Extent	1 online resource
336 ## - CONTENT TYPE
Content type term	text
Content type code	txt
Source	rdacontent
337 ## - MEDIA TYPE
Media type term	computer
Media type code	c
Source	rdamedia
338 ## - CARRIER TYPE
Carrier type term	online resource
Carrier type code	cr
Source	rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type	text file
Encoding format	PDF
Source	rda
490 1# - SERIES STATEMENT
Series statement	T-Labs Series in Telecommunication Services,
International Standard Serial Number	2192-2829
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note	1. Introduction -- 2. Quality Assessment of Transmitted Speech -- 3. Neural Network Architectures for Speech Quality Prediction -- 4. Double-Ended Speech Quality Prediction Using Siamese Networks -- 5. Prediction of Speech Quality Dimensions With Multi-Task Learning -- 6. Bias-Aware Loss for Training From Multiple Datasets -- 7. NISQA – A Single-Ended Speech Quality Model -- 8. Conclusions -- A. Dataset Condition Tables -- B. Train and Validation Dataset Dimension Histograms -- References.
520 ## - SUMMARY, ETC.
Summary, etc.	This book presents how to apply recent machine learning (deep learning) methods for the task of speech quality prediction. The author shows how recent advancements in machine learning can be leveraged for the task of speech quality prediction and provides an in-depth analysis of the suitability of different deep learning architectures for this task. The author then shows how the resulting model outperforms traditional speech quality models and provides additional information about the cause of a quality impairment through the prediction of the speech quality dimensions of noisiness, coloration, discontinuity, and loudness.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element	Signal processing.

Topical term or geographic name entry element	User interfaces (Computer systems).

Topical term or geographic name entry element	Human-computer interaction.

Topical term or geographic name entry element	Natural language processing (Computer science).

Topical term or geographic name entry element	Acoustical engineering.

Topical term or geographic name entry element	Digital and Analog Signal Processing.

Topical term or geographic name entry element	User Interfaces and Human Computer Interaction.

Topical term or geographic name entry element	Natural Language Processing (NLP).

Topical term or geographic name entry element	Engineering Acoustics.
653 #0 - INDEX TERM--UNCONTROLLED
Uncontrolled term	Deep learning (Machine learning)

Uncontrolled term	Speech processing systems
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element	SpringerLink (Online service)
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title	T-Labs Series in Telecommunication Services,
International Standard Serial Number	2192-2829
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier	<a href="https://doi.org/10.1007/978-3-030-91479-0">https://doi.org/10.1007/978-3-030-91479-0</a>
Materials specified	Springer eBooks
Public note	Online access link to the resource
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme	Library of Congress Classification
Koha item type	E-Book

Holdings
Withdrawn status	Lost status	Source of classification or shelving scheme	Not for loan	Collection code	Home library	Current library	Date acquired	Source of acquisition	Coded location qualifier	Inventory number	Total Checkouts	Full call number	Barcode	Date last seen	Copy number	Date shelved	Koha item type	Public note
		Library of Congress Classification	Geçerli değil-e-Kitap / Not applicable-e-Book	E-Kitap Koleksiyonu	Merkez Kütüphane	Merkez Kütüphane	11/10/2023	Satın Alma / Purchase		BİL/YAP		Q325.73EBK	EBK02922	16/11/2023	1	16/11/2023	E-Book