Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Segment boundary detection via class entropy measurements in connectionist phoneme recognition
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-3323-5311
2006 (English)In: Speech Communication, ISSN 0167-6393, E-ISSN 1872-7182, Vol. 48, no 12, 1666-1676 p.Article in journal (Refereed) Published
Abstract [en]

This article investigates the possibility to use the class entropy of the output of a connectionist phoneme recogniser to predict time boundaries between phonetic classes. The rationale is that the value of the entropy should increase in proximity of a transition between two segments that are well modelled (known) by the recognition network since it is a measure of uncertainty. The advantage of this measure is its simplicity as the posterior probabilities of each class are available in connectionist phoneme recognition.The entropy and a number of measures based on differentiation of the entropy are used in isolation and in combination. The decision methods for predicting the boundaries range from simple thresholds to neural network based procedure.The different methods are compared with respect to their precision, measured in terms of the ratio between the number C of predicted boundaries within 10 or 20 ms of the reference and the total number of predicted boundaries, and recall, measured as the ratio between C and the total number of reference boundaries.

Place, publisher, year, edition, pages
2006. Vol. 48, no 12, 1666-1676 p.
Keyword [en]
boundary detection, entropy, connectionist phoneme recognition, speech recognition
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-16250DOI: 10.1016/j.specom.2006.07.009ISI: 000243246600006Scopus ID: 2-s2.0-37849185609OAI: oai:DiVA.org:kth-16250DiVA: diva2:334292
Conference
International Conference on Non-Linear Speech Processing. Barcelona, SPAIN. APR 19-22, 2005
Note

QC 20100525, QC 20110929

Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2017-12-12Bibliographically approved

Open Access in DiVA

segmentboundarydetection(564 kB)104 downloads
File information
File name FULLTEXT01.pdfFile size 564 kBChecksum SHA-512
49e08897aae1316e6c42fe6775ea1e3a62ed705593d1be1f09544d6e3c32fd6eef2c495a55ca7462ed18ebe044fd5a3500eb348254fac39aec37ab796c500060
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records BETA

Salvi, Giampiero

Search in DiVA

By author/editor
Salvi, Giampiero
By organisation
Speech Communication and Technology
In the same journal
Speech Communication
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 104 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 64 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf