Comparison of Current Frame-Based Phoneme Classifiers
|
| Title | Comparison of Current Frame-Based Phoneme Classifiers |
| Authors | |
| Abstract | This paper compares today’s most common frame-based classifiers. These classifiers can be divided into the two main groups – generic classifiers which creates the most probable model based on the training data (for example GMM) and discriminative classifiers which focues on creating decision hyperplane. A lot of research has been done with the GMM classifiers and therefore this paper will be mainly focused on the frame-based classifiers. Two discriminative classifiers will be presented. These classifiers implements a hieararchical tree root structure over the input phoneme group which shown to be an effective. Based on these classifiers, two efficient training algorithms will be presented. We demonstrate advantages of our training algorithms by evaluating all classifiers over the TIMIT speech corpus. |
| Publisher | Faculty of Electrical Engineering and Computer Science |
| Date | 2011-12-27 |
| Source | Advances in Electrical and Electronic Engineering Vol 9, No 5 (2011): Special Issue |
| Rights | Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the works authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journals published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access). |