Speech recognition consists of converting input sound into a sequence phonemes, then finding text for the using language models. Therefore, phoneme classification performance is critical factor successful implementation speech system. However, correctly distinguishing phonemes with similar characteristics still challenging problem even state-of-the-art methods, and errors are hard to be recover...

In machine learning and data mining, most of the works in classification problems deal with flat classification, where each instance is classified in one of a set of possible classes and there is no hierarchical relationship between the classes. There are, however, more complex classification problems where the classes to be predicted are hierarchically related. This chapter presents a tutorial...

Hierarchical text classification refers to assigning text documents to the categories in a given category tree based on their content. With large number of categories organized as a tree, hierarchical text classification helps users to find information more quickly and accurately. Nevertheless, hierarchical text classification methods in the past have often been constructed in a proprietary man...

A framework for deriving high-level scene attributes from low-level image features is presented. The assignment of the attributes to images is done by a hierarchical classification of the low level features, which capture colour, texture and spatial information. A system for image classification is implemented, which aids in the evaluation of the different methods available. A detailed analysis...