Udvidet returret til d. 31. januar 2025

Feature-based Robust Techniques for Speech Recognition System - Amitoj Singh - Bog

Feature-based Robust Techniques for Speech Recognition Systemaf Amitoj Singh
Bag om Feature-based Robust Techniques for Speech Recognition System

Punjabi language is popular Indo-Aryan language. Its phoneme sounds are tonal in nature which dissent in almost all-Indian side of Punjab. This books focus on analysis of some pf the dominant feature extraction techniques used in Automatic Speech Recognition and analytically analyse which feature extraction techniques is best suitable for extracting features of the tone present in the Punjabi speech. Three feature extractions techniques are compared: ¿power normalized cepstral coefficients (PNCC)¿, ¿Mel frequency cepstral coefficients (MFCC)¿ and ¿Perceptual Linear Prediction (PLP)¿ following a statistical comparison based on the accuracy and correctness of results attained. To attain a higher rate of accuracy level 34 phones for Punjabi language are used to break each word into small sound frames. environments using evident number of speakers giving overall system results with MFCC as finest of all three in noise-free environment and PLP to be efficient feature extraction technique in noisy environment for Punjabi speech corpus.

Vis mere
  • Sprog:
  • Engelsk
  • ISBN:
  • 9783659960253
  • Indbinding:
  • Paperback
  • Sideantal:
  • 60
  • Udgivet:
  • 26. september 2018
  • Størrelse:
  • 150x4x220 mm.
  • Vægt:
  • 107 g.
  • 2-3 uger.
  • 3. december 2024
På lager

Normalpris

  • BLACK NOVEMBER

Medlemspris

Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Feature-based Robust Techniques for Speech Recognition System

Punjabi language is popular Indo-Aryan language. Its phoneme sounds are tonal in nature which dissent in almost all-Indian side of Punjab. This books focus on analysis of some pf the dominant feature extraction techniques used in Automatic Speech Recognition and analytically analyse which feature extraction techniques is best suitable for extracting features of the tone present in the Punjabi speech. Three feature extractions techniques are compared: ¿power normalized cepstral coefficients (PNCC)¿, ¿Mel frequency cepstral coefficients (MFCC)¿ and ¿Perceptual Linear Prediction (PLP)¿ following a statistical comparison based on the accuracy and correctness of results attained. To attain a higher rate of accuracy level 34 phones for Punjabi language are used to break each word into small sound frames. environments using evident number of speakers giving overall system results with MFCC as finest of all three in noise-free environment and PLP to be efficient feature extraction technique in noisy environment for Punjabi speech corpus.

Brugerbedømmelser af Feature-based Robust Techniques for Speech Recognition System



Gør som tusindvis af andre bogelskere

Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.