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
On Acquiring Speech Production Knowledge from Articulatory Measurements for Phoneme Recognition
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
2009 (English)In: INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, BAIXAS: ISCA-INST SPEECH COMMUNICATION ASSOC , 2009, 1387-1390 p.Conference paper, Published paper (Refereed)
Abstract [en]

The paper proposes a general version of a coupled Hidden Markov/Bayesian Network model for performing phoneme recognition on acoustic-articulatory data. The model uses knowledge learned from the articulatory measurements, available for training, for phoneme recognition on the acoustic input. After training on the articulatory data, the model is able to predict 71.5% of the articulatory state sequences using the acoustic input. Using optimized parameters, the proposed method shows a slight improvement for two speakers over the baseline phoneme recognition system which does not use articulatory knowledge. However, the improvement is only statistically significant for one of the speakers. While there is an improvement in recognition accuracy for the vowels, diphthongs and to some extent the semi-vowels, there is a decrease in accuracy for the remaining phonemes.

Place, publisher, year, edition, pages
BAIXAS: ISCA-INST SPEECH COMMUNICATION ASSOC , 2009. 1387-1390 p.
Keyword [en]
phoneme recognition, articulatory measurements, Coupled-HMM
National Category
Computer and Information Science General Language Studies and Linguistics
Identifiers
URN: urn:nbn:se:kth:diva-29882ISI: 000276842800344Scopus ID: 2-s2.0-70450202220OAI: oai:DiVA.org:kth-29882DiVA: diva2:399061
Conference
10th INTERSPEECH 2009 Conference, Brighton, ENGLAND, SEP 06-10, 2009
Note
QC 20110221Available from: 2011-02-21 Created: 2011-02-17 Last updated: 2011-02-21Bibliographically approved

Open Access in DiVA

No full text

Other links

ScopusISCA

Search in DiVA

By author/editor
Neiberg, DanielAnanthakrishnan, GopalBlomberg, Mats
By organisation
Speech Communication and Technology
Computer and Information ScienceGeneral Language Studies and Linguistics

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 35 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