Conventional speaker-independent HMMs ignore the speaker di erences and collect speech data in an observation space. This causes a problem that the output probability distribution of the HMMs becomes vague so that it deteriorates the recognition accuracy. To solve this problem, we construct the speaker subspace for an individual speaker and correlate them by o-space canonical correlation analys...

This paper provides an overview of Kernel Canonical Correlation Analysis. KCCA is a technique for finding common semantic features between different views of data. Applications on text retrieval, categorization and image retrieval based on text queries are presented.

We consider several stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the current projection of one data set as the target for the other and then repeat in the opposite direction. The second uses a method which relies on probabilistically sphering the data, concatenating the two streams and...

Phalaenopsis is an important genus of orchids that is grown for economical production of cut flower and potted plants. The objective of this study is the evaluation of correlation between morphological and physiological traits of self and cross-pollination of 5 varieties of Phalaenopsis orchid. Some morphological traits were measured: Capsule length (CL), capsule volume (CV), weight of seeds in...

Corticomuscular activity modeling based on multiple data sets such as electroencephalography (EEG) and electromyography (EMG) signals provides a useful tool for understanding human motor control systems. In this paper, we propose modeling corticomuscular activity by combining partial least squares (PLS) and canonical correlation analysis (CCA).The proposed method takes advantage of both PLS and...

The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information. Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT). A new approach is proposed to further analyse and impr...