Date of Original Version

5-2013

Type

Conference Proceeding

Journal Title

Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing

First Page

8111

Last Page

8115

Rights Management

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Abstract or Description

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding zero resource (unsupervised) speech technologies and related models of early language acquisition. Centered around the tasks of phonetic and lexical discovery, we consider unified evaluation metrics, present two new approaches for improving speaker independence in the absence of supervision, and evaluate the application of Bayesian word segmentation algorithms to automatic subword unit tokenizations. Finally, we present two strategies for integrating zero resource techniques into supervised settings, demonstrating the potential of unsupervised methods to improve mainstream technologies.

DOI

10.1109/ICASSP.2013.6639245

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Published In

Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 8111-8115.