English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper presents a new hierarchical phoneme recognition system using the SVM classifier and different feature representations based on mellin transform. The proposed architecture uses different representations with each group of phonemes of the speech database TIMIT which are distributed in a way to reduce the confusions between phonemes having similar articulatory strcuture. The main idea of this new architecture is based on the principle that each group of phonemes has his own characteristics which requires us to choose the adequate representation for the given group. Experiments have proven the robustness of our new hierarchical phoneme recognition system (called MMP) and the use of conventional feature representations based on mellin transform explains its superior recognition performance.

Phoneme Classification Using New Feature Extraction Techniques based on Mellin Transform