feature based robust techniques speech von singh amitoj (6 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch.

Paperback. Zustand: Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock.

paperback. Zustand: New. New. book.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 60 pp. Englisch.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh AmitojAmitoj Singh is Doctorate in computer science and working as Assistant Professor in the department of computational Sciences, MRSPTU, Punjab India. With over 12 years f experience, he has filed 04 Patent, published 32 nat.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.