AES E-Library

AES E-Library

Designing Optimal Phoneme-Wise Fuzzy Cluster Analysis

A large number of pattern classification algorithms and methodologies have been proposed for the phoneme recognition task during the last decades. The current paper presents a prototype distance-based fuzzy classifier, optimized for the needs of phoneme recognition. This is accomplished by the specially designed objective function and a respective training strategy. Particularly, each phonemic class is represented by a number of arbitrary-shaped clusters which adaptively match the corresponding features space distribution. The formulation of the approach is capable of delivering a variety of related conclusions based on fuzzy logic arithmetic. An overview of the inference capability is presented in combination with performance results for the Greek language.

AES Convention: Paper Number:
Publication Date:

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

AES - Audio Engineering Society