東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Real-time speech and music classific...

Eyben, Florian.

Linked to FindBook

Google Book

Amazon

博客來

Real-time speech and music classification by large audio feature space extraction

Record Type:	Electronic resources : Monograph/item
Title/Author:	Real-time speech and music classification by large audio feature space extraction/ by Florian Eyben.
Author:	Eyben, Florian.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xxxviii, 298 p. :ill., digital ;24 cm.
[NT 15003449]:	Abstract -- Introduction -- Acoustic Features and Modelling -- Standard Baseline Feature Sets -- Real-time Incremental Processing -- Real-life Robustness -- Evaluation -- Discussion and Outlook -- Appendix -- Mel-frequency Filterbank Parameters.
Contained By:	Springer eBooks
Subject:	Automatic speech recognition. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-27299-3
ISBN:	9783319272993$q(electronic bk.)

Real-time speech and music classification by large audio feature space extraction
Eyben, Florian.

Real-time speech and music classification by large audio feature space extraction[electronic resource] /by Florian Eyben. - Cham :Springer International Publishing :2016. - xxxviii, 298 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Abstract -- Introduction -- Acoustic Features and Modelling -- Standard Baseline Feature Sets -- Real-time Incremental Processing -- Real-life Robustness -- Evaluation -- Discussion and Outlook -- Appendix -- Mel-frequency Filterbank Parameters.

This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the automated analysis and classification of speech and music. It defines several standard acoustic parameter sets and describes their implementation in a novel, open-source, audio analysis framework called openSMILE, which has been accepted and intensively used worldwide. The book offers extensive descriptions of key methods for the automatic classification of speech and music signals in real-life conditions and reports on the evaluation of the framework developed and the acoustic parameter sets that were selected. It is not only intended as a manual for openSMILE users, but also and primarily as a guide and source of inspiration for students and scientists involved in the design of speech and music analysis methods that can robustly handle real-life conditions.

ISBN: 9783319272993$q(electronic bk.)

Standard No.: 10.1007/978-3-319-27299-3doiSubjects--Topical Terms:

753709
Automatic speech recognition.

LC Class. No.: TK7895.S65

Dewey Class. No.: 006.454

Real-time speech and music classification by large audio feature space extraction
LDR:02180nmm a2200349 a 4500 001 2029915
003 DE-He213
005 20160808165600.0
006 m d
007 cr nn 008maaau
008 160908s2016 gw s 0 eng d
020 $a 9783319272993$q(electronic bk.)
020 $a 9783319272986$q(paper)
024 7 $a 10.1007/978-3-319-27299-3 $2 doi
035 $a 978-3-319-27299-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7895.S65
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 006.454 $2 23
090 $a TK7895.S65 $b E97 2016
100 1 $a Eyben, Florian. $3 2181223
245 1 0 $a Real-time speech and music classification by large audio feature space extraction $h [electronic resource] / $c by Florian Eyben.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xxxviii, 298 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Abstract -- Introduction -- Acoustic Features and Modelling -- Standard Baseline Feature Sets -- Real-time Incremental Processing -- Real-life Robustness -- Evaluation -- Discussion and Outlook -- Appendix -- Mel-frequency Filterbank Parameters.
520 $a This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the automated analysis and classification of speech and music. It defines several standard acoustic parameter sets and describes their implementation in a novel, open-source, audio analysis framework called openSMILE, which has been accepted and intensively used worldwide. The book offers extensive descriptions of key methods for the automatic classification of speech and music signals in real-life conditions and reports on the evaluation of the framework developed and the acoustic parameter sets that were selected. It is not only intended as a manual for openSMILE users, but also and primarily as a guide and source of inspiration for students and scientists involved in the design of speech and music analysis methods that can robustly handle real-life conditions.
650 0 $a Automatic speech recognition. $3 753709
650 0 $a Human-computer interaction. $3 560071
650 1 4 $a Engineering. $3 586835
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a User Interfaces and Human Computer Interaction. $3 892554
650 2 4 $a Engineering Acoustics. $3 1533220
650 2 4 $a Computational Linguistics. $3 893900
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer theses. $3 1314442
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-27299-3
950 $a Engineering (Springer-11647)