Gender Clustering Improvement for Speaker Adaptation Using LDA
Seyed Omid Sadjadi, Oldooz Hazrati, Karim Faez · 2007
Abstract: Speaker adaptation is an important issue in current speech recognition researches. Speaker clustering is one of the widely used methods in speaker adaptation. In this paper the effect of Linear Discriminant Analysis (LDA) on increasing the accuracy of some clustering methods such as k-means and Support Vector Machine (SVM) is demonstrated. The performance of this idea was examined on AURORA 2.0 (clean version) dataset that is one of the most popular datasets used for speech recognition and processing aims.