All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Improved Estimation of Articulatory Features Based on Acoustic Features with Temporal Context

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00232103" target="_blank" >RIV/68407700:21230/15:00232103 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007/978-3-319-24033-6_63" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-24033-6_63</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-24033-6_63" target="_blank" >10.1007/978-3-319-24033-6_63</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improved Estimation of Articulatory Features Based on Acoustic Features with Temporal Context

  • Original language description

    The paper deals with neural network-based estimation of articulatory features for Czech which are intended to be applied within automatic phonetic segmentation or automatic speech recognition. In our current approach we use the multi-layer perceptron networks to extract the articulatory features on the basis of non-linear mapping from standard acoustic features extracted from speech signal. The suitability of various acoustic features and the optimum length of temporal context at the input of used network were analysed. The temporal context is represented by a context window created from the stacked feature vectors. The optimum length of the temporal contextual information was analysed and identified for the context window in the range from 9 to 21 frames.We obtained 90.5% frame level accuracy on average across all the articulatory feature classes for mellog filter-bank features. The highest classification rate of 95.3% was achieved for the voicing class.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JA - Electronics and optoelectronics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Text, Speech, and Dialogue. 18th International Conference, TSD 2015

  • ISBN

    978-3-319-24032-9

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    560-568

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Plzen

  • Event date

    Sep 14, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000365947800063