Virtual machines and containers as a platform for experimentation

Conference Paper

Research on computational speech processing has traditionally relied on the availability of a relatively large and complex infrastructure, which encompasses data (text and audio), tools (feature extraction, model training, scoring, possibly on-line and off-line, etc.), glue code, and computing. Traditionally, it has been very hard to move experiments from one site to another, and to replicate experiments. With the increasing availability of shared platforms such as commercial cloud computing platforms or publicly funded super-computing centers, there is a need and an opportunity to abstract the experimental environment from the hardware, and distribute complete setups as a virtual machine, a container, or some other shareable resource, that can be deployed and worked with anywhere. In this paper, we discuss our experience with this concept and present some tools that the community might find useful. We outline, as a case study, how such tools can be applied to a naturalistic language acquisition audio corpus.

Full Text

Duke Authors

Cited Authors

  • Metze, F; Riebling, E; Warlaumont, AS; Bergelson, E

Published Date

  • January 1, 2016

Published In

Volume / Issue

  • 08-12-September-2016 /

Start / End Page

  • 1603 - 1607

Electronic International Standard Serial Number (EISSN)

  • 1990-9772

International Standard Serial Number (ISSN)

  • 2308-457X

Digital Object Identifier (DOI)

  • 10.21437/Interspeech.2016-997

Citation Source

  • Scopus