Development and application of an accurate and flexible automatic aligner

Abstract

Large databases are useful tools for speech technology research. Their usefulness is greatly enhanced if the data is annotated with time aligned labels. This is expensive and time consuming and has lead to the investigation and development of automatic aligners. This paper reports on an automatic aligner developed initially to solve the problem of annotating a large database within a set period of time. While developing the aligner, we investigated the importance of the models, the use of manual labels to bootstrap the system, and the role of the dictionary in the effectiveness of the aligner, and found that each had a contribution to make. The aligner produced was tested on unseen data to gauge its accuracy before being applied as a tool to annotation of a large amount of data. The aligner was developed in a way that facilitates its use in other applications.