Weighted Entropy Cortical Algorithms for Modern Standard Arabic Speech Recognition
نویسنده
چکیده
Cortical algorithms (CA) inspired by and modeled after the human cortex, have shown superior accuracy in few machine learning applications. However, CA have not been extensively implemented for speech recognition applications, in particular the Arabic language. Motivated to apply CA to Arabic speech recognition, we present in this paper an improved CA that is efficiently trained using an entropy-based cost function, and an entropy based weight update rule. We modify the strengthening and inhibiting rules originally employed in CA during feedback training with weighted entropy concepts. Preliminary results show the merit of the proposed modifications in the recognition of isolated Arabic speech and motivate follow on research. Keywords—Cortical algorithms, Isolated Arabic Speech Recognition, Entropy cost function, Entropy Weight Update Rule.
منابع مشابه
Classifying and Segmenting Classical and Modern Standard Arabic using Minimum Cross-Entropy
Text classification is the process of assigning a text or a document to various predefined classes or categories to reflect their contents. With the rapid growth of Arabic text on the Web, studies that address the problems of classification and segmentation of the Arabic language are limited compared to other languages, most of which implement word-based and feature extraction algorithms. This ...
متن کاملOff-line Arabic Handwritten Recognition Using a Novel Hybrid HMM-DNN Model
In order to facilitate the entry of data into the computer and its digitalization, automatic recognition of printed texts and manuscripts is one of the considerable aid to many applications. Research on automatic document recognition started decades ago with the recognition of isolated digits and letters, and today, due to advancements in machine learning methods, efforts are being made to iden...
متن کاملColloquialising Modern Standard Arabic Text for Improved Speech Recognition
Modern standard Arabic (MSA) is the official language of spoken and written Arabic media. Colloquial Arabic (CA) is the set of spoken variants of modern Arabic that exist in the form of regional dialects. CA is used in informal and everyday conversations while MSA is formal communication. An Arabic speaker switches between the two variants according to the situation. Developing an automatic spe...
متن کاملCross-Dialectal Data Transferring for Gaussian Mixture Model Training in Arabic Speech Recognition
Dialectal Arabic speech recognition is a difficult problem and is relatively less studied. In this paper, we propose a cross-dialectal Gaussian mixture model training criteria to transfer knowledge from one domain to the other by data sharing. Specifically, phone classification experiments on West Point Modern Standard Arabic Speech corpus and Babylon Levantine Arabic Speech corpus demonstrate ...
متن کاملExperiments on Automatic Recognition of Nonnative Arabic Speech
The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of n...
متن کامل