Arkadiusz Nagórski

Learn More
This paper presents a method designed to select a limited set of maximally information rich speech data from a database for optimal training and diagnostic testing of Automatic Speech Recognition (ASR) systems. The method uses Principal Component Analysis (PCA) to map the variance of the speech material in a database into a low-dimensional space, followed(More)
This paper presents an extended study in the topic of optimal selection of speech data from a database for efficient training of ASR systems. We reconsider a method of optimal selection introduced in our previous work and introduce variosearch as an alternative selection method developed in order to find a representative sample of speech data with a(More)
In this paper, assessment of ASR systems with a limited set of speech data selected from a larger testing corpus was studied for connected Dutch digits. Three methods of data selection were applied, namely random, knowledge-based, and data-driven selection. The goal of this study was to find out whether reliable assessment of speech recognition systems can(More)
  • 1