Students at Monash University used Alveo as part of an introductory course in computational linguistics this year. The students completed an assignment which used basic techniques of corpus linguistics to compare one phenomenon in varieties of English.
NeCTAR have just published a story on their news page about the Alveo Launch including the video above where I am interviewed about the work that is supported by Alveo.
A brief tour of Alveo made for the official launch on 1 July 2014.
Alveo presentation, Open Repositories 2014 by Steve Cassidy,Dominique Estival, Peter Sefton, Jared Berghold & Denis Burnham is licensed under a Creative Commons Attribution 4.0 International License.
Presentation delivered by Peter Sefton at Open Repositories 2014 in Helsinki
Preceding the official launch of Alveo on July 1 we will be holding a Hackfest for a hands-on day with Alveo. We hope the outcome of the day will be some exciting ideas and maybe even the start of some interesting research outcomes using data from the Alveo repository.
The Alveo Virtual Laboratory is an eResearch project funded
under the Australian Government NeCTAR program to build a platform for collaborative eResearch around
data representing human communication and the tools that researchers use in their analysis. The human
communication science field is broadly defined to encompass the study of language from various
perspectives but also includes research on music and various other forms of human expression.
This paper outlines the core architecture of the Alveo and in
particular, highlights the web based API that provides access to data and
tools to authenticated users.
This work by Steve Cassidy, Dominique Estival, Tim Jones, Peter Sefton, Denis Burnham and Jared Berghold is licensed under a Creative Commons Attribution 4.0 International License.
This work by Peter Sefton, Steve Cassidy, Dominique Estival, Jared Berghold & Denis Burnham is licensed under a Creative Commons Attribution 4.0 International License.
This presentation about the HCS Vlab was delivered by Peter Sefton at Digital Humanities Australasia 2014 in Perth
I just received a report from Matt Atcheson, one of our HDR testers at UWA, with the results of some work he’s done on evaluating the HTK integration with the HCS vLab. Matt used my template Python interface to download audio files from the vLab and feed them to the HTK training algorithms to train a digit string recogniser. He was then able to test the recogniser on unknown data also downloaded from the vLab.
The results were interesting:
Using the full set of digit recordings that I could find (about 940 of them), setting aside 10% for testing, and with a grammar that constrains transcripts to exactly four digits, I get about 99% word accuracy, and about 95% sentence accuracy.
====================== HTK Results Analysis =======================Date: Tue Jan 28 21:08:50 2014Ref : >ntu/hcsvlab_api_testing_matt/
digitrec/data/testing_files/ testref1.mlfRec : >buntu/hcsvlab_api_testing_ matt/digitrec/data/testing_ files/recout.mlf———————— Overall Results ————————–SENT: %Correct=94.74 [H=90, S=5, N=95]WORD: %Corr=98.95, Acc=98.42 [H=564, D=3, S=3, I=3, N=570]
[This User Experience review of the HCS VLab code is posted with the permission of the Author and AeRO, the group who commissioned the review]
Reviewer: Sam Wolski, eResearch Services, Griffith University firstname.lastname@example.org OS: OSX 10.8.2 Browser: Chrome 29.0.1547.65 Test Case(s): Supplied ‘HCS vLab Testing August’ document.
The HCS vLab is easily one of the best interfaces I’ve come across in Australian research projects and eResearch applications. The Bootstrap framework is a great development platform and the workflows and interfaces of the HCS vLab have been integrated well to form a beautifully clean and usable application. The following feedback is intended to provide a list of small improvements to the application. Continue reading