John Kominek

Multimodal people ID for a multimedia meeting browser

A meeting browser is a system that allows users to review a multimedia meeting record from a variety of indexing methods. Identification of meeting participants is essential for creating such a multimedia meeting record. Moreover, knowing who is speaking can enhance the performance of speech recognition and indexing meeting transcription. In this paper, we present an approach that identifies meeting participants by fusing multimodal inputs. We use face ID, speaker ID, color appearance ID, and sound source directional ID to identify and track meeting. After describing the different modules in detail, we will discuss a framework for combining the information sources. Integration of the multimodal people ID into the multimedia meeting browser is in its preliminary stage.

Learning Pronunciation Dictionaries: Language Complexity and Word Selection Strategies

The speed with which pronunciation dictionaries can be bootstrapped depends on the efficiency of learning algorithms and on the ordering of words presented to the user. This paper presents an active-learning word selection strategy that is mindful of human limitations. Learning rates approach that of an oracle system that knows the final LTS rule set.

Optimizing segment label boundaries for statistical speech synthesis

This paper introduces a new optimization technique for moving segment labels (phone and subphonetic) to optimize statistical parametric speech synthesis models. The choice of objective measures is investigated thoroughly and listening tests show the results to significantly improve the quality of the generated speech equivalent to increasing the database size by 3 fold.