Abstract: Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.
Abstract: The paper presents the design concept of a unitselection
text-to-speech synthesis system for the Slovenian language.
Due to its modular and upgradable architecture, the system can be
used in a variety of speech user interface applications, ranging from
server carrier-grade voice portal applications, desktop user interfaces
to specialized embedded devices.
Since memory and processing power requirements are important
factors for a possible implementation in embedded devices, lexica
and speech corpora need to be reduced. We describe a simple and
efficient implementation of a greedy subset selection algorithm that
extracts a compact subset of high coverage text sentences. The
experiment on a reference text corpus showed that the subset
selection algorithm produced a compact sentence subset with a small
redundancy.
The adequacy of the spoken output was evaluated by several
subjective tests as they are recommended by the International
Telecommunication Union ITU.