MARC details
000 -LEADER |
fixed length control field |
03615nam a22005655i 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
TR-AnTOB |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20231121163655.0 |
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 |
211005s2022 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783030807412 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-3-030-80741-2 |
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 |
TK7895.S65 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
TJF |
Source |
bicssc |
|
Subject category code |
UYU |
Source |
bicssc |
|
Subject category code |
TEC008000 |
Source |
bisacsh |
|
Subject category code |
TJF |
Source |
thema |
|
Subject category code |
UYU |
Source |
thema |
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TK7882.S65EBK |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Manjunath, K.E. |
Relator term |
author. |
Relator code |
aut |
-- |
http://id.loc.gov/vocabulary/relators/aut |
245 10 - TITLE STATEMENT |
Title |
Multilingual Phone Recognition in Indian Languages |
Medium |
[electronic resource] / |
Statement of responsibility, etc. |
by K.E Manjunath. |
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 |
SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |
International Standard Serial Number |
2191-7388 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
1. Introduction -- 2. Literature review -- 3. Development and analysis of Multilingual Phone recognition system -- 4. Prediction of Multilingual Articulatory Features -- 5. Articulatory Features of Multilingual Phone recognition -- 6. Applications of Multilingual Phone recognition in Code-switched and Non-code-switched Scenarios -- 7. Summary and Conclusion. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN). Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Speech processing systems. |
|
Topical term or geographic name entry element |
Signal processing. |
|
Topical term or geographic name entry element |
Natural language processing (Computer science). |
|
Topical term or geographic name entry element |
Computational linguistics. |
|
Topical term or geographic name entry element |
Speech and Audio Processing. |
|
Topical term or geographic name entry element |
Natural Language Processing (NLP). |
|
Topical term or geographic name entry element |
Computational Linguistics. |
653 #0 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Automatic speech recognition |
|
Uncontrolled term |
Computational linguistics -- India |
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 |
SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, |
International Standard Serial Number |
2191-7388 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="https://doi.org/10.1007/978-3-030-80741-2">https://doi.org/10.1007/978-3-030-80741-2</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 |