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SylNet: An Adaptable End-to-End Syllable Count Estimator for Speech

Year of publication

2019

Authors

Seshadri, Shreyas; Räsänen, Okko

Organizations and authors

Tampere University

Räsänen Okko

Aalto University

Räsänen Okko

Seshadri Shreyas

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal/Series

IEEE signal processing letters

Publisher

Volume

26

Issue

9

Pages

1359-1363

ISSN

Publication forum

Publication forum level

2

Open access

Open access in the publisher’s service

No

Self-archived

Yes

Other information

Fields of science

Statistics and probability; Computer and information sciences

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object]

Internationality of the publisher

International

Language

English

International co-publication

No

Co-publication with a company

No

DOI

10.1109/LSP.2019.2929415

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes