Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Multiple Timescale Feature Combination towards Robust Speech Recognition
 
conference paper

Multiple Timescale Feature Combination towards Robust Speech Recognition

Weber, Katrin
2000
KONVENS 2000 / Sprachkommunikation
KONVENS 2000 / Sprachkommunikation

While a lot of progress has been made during the last years in the field of Automatic Speech recognition (ASR), one of the main remaining problems is that of robustness. Typically, state-of-the-art ASR systems work very efficiently in well-defined environments, e.g. for clean speech or known noise conditions. However, their performance degrades drastically under different conditions. Many approaches have been developed to circumvent this problem, ranging from noise cancellation to system adaptation techniques. This paper investigates the influence of using additional information from relatively long timescales to noise robustness. The multiple timescale feature combination approach is introduced. Experiments show that, while maintaining recognition performance for clean speech, robustness could be improved in noisy conditions.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

rr00-29.pdf

Access type

openaccess

Size

40.35 KB

Format

Adobe PDF

Checksum (MD5)

b2e0b1a0d69646d5c376f6f1bdea18f0

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés