CALO Decoder Progress Report for March Arthur (Decoder and ICSI Training) Jahanzeb (Decoder) Ziad (ICSI Training) Moss (ICSI Training) Carnegie Mellon.

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Presentation transcript:

CALO Decoder Progress Report for March Arthur (Decoder and ICSI Training) Jahanzeb (Decoder) Ziad (ICSI Training) Moss (ICSI Training) Carnegie Mellon University Apr 13, 2004

This Presentation  Progress report for March  In February Batch mode recognizer completed Live-mode recognizer didn ’ t work  In March More decoder work  Speed, Accuracy, Interface. ICSI transcription conversion task  Resources, Conversion Scripts Miscellaneous efforts in improving the decoder  Contact with other groups, web page(s), manual.

Decoder work (Speed)  By Arthur and Jahanzeb  Sphinx 3.4 starts to work reasonably in Communicator task 1G: 1.1xRT, 2G: 0.48xRT  Phoneme look-ahead research completed 15-20% gain when CIGMMS applied Will incorporate as a functionality  Outlook of April Machine Optimization (Still there!) WSJ evaluation Technical report version of the results publishing.

Decoder work (Accuracy)  First comparison between s2 and s3.4 S3.0 ~ S2 > S3.3 > S3.4 Not the fairest comparison  S3 model is trained by female speakers only  S3 model is less tuned  Outlook of April Learn how to do training. Do a fairer comparison. Change search structure.

Decoder work (Interface)  Live-mode decoder works Live-mode recognizer interface is still poorer than S2 No config file yet. Many users complained (Well, actually 2-3 of them)  Outlook of April Focus on building better API-interface and command-line interface. Jahanzeb will be there while Arthur is working on training.

ICSI Training  Transcription Conversion Task  By Moss, Ziad and Arthur  Completion of Resource mapping (100%) OOV (~20%) Conversion script (90%)

ICSI Transcription: How does it look like?   three six two four three zero seven 

XML tags conversion  Transcription is more detail than necessary.  Current Treatment: : Ignore whole sentence. Too many occurrences, too many varieties.. : Ignore. : Replace by ++GARBAGE++ : Ignore whole sentence. Too few occurrence. Don ’ t want to care : Replace by ++GARBAGE++ & : Use mapping.

Plain-text Normalization  After XML Conversion “ I – I am no-, I mean C-zero ”  ‘ - ’ can mean “ - ” : Interruption/Interjection marks “ -XXX ” or “ XXX- ” : Broken words “ XXX-XXX ” : hyphenated words  AM transcription Get rid all pronunciations and leave broken words alone  LM transcription Interruption marks and broken words will be removed (Optional) Leave interruption marks there.

XML conversion script  Functionalities Optional conversion Resource (dict/mapping/rules) read-in XML parser Generate both transcription and control file for close-talking microphones Generate both LM and AM transcription  TODO: Incorporate Ziad ’ s script  Correct timing information  Generation of far-field channels Fix small bugs.

Outlook of ICSI training task in April  Complete OOVs transcription (Arthur, Moss and Ziad)  Fix bugs in conversion script (Arthur  Learn AM training (Ziad and Arthur)  LM training (Moss)  Fix potential problems in SphinxTrain.

Miscellaneous (Contact with other group)  Want to seek a better interface for Sphinx  Try to contact other groups to see what ’ s up  XVoice-sphinx, “ command-and-control ” application that tried to use Sphinx. Actually it does dictation. Not very happy with Sphinx after Sphinx ’ s default AM and LM in command-and-control  OSSRI No clear goal yet Start to gather funding. Don ’ t really like Sphinx because “ Sphinx is poorer than ViaVoice in C&C ”

We need to help them more ……  We need better …… Release (to replace s3.3)  After WSJ evaluation, S3.4 will officially released to replace the current S3.3 Sphinx web page (also CMU web page)  Sphinx ’ s web page need to have a more unified theme.  Task force will be gathered after ICSLP Manual  Need to provide basic education to developers and “ hard-core ” hackers.  wrote the first outline of the manual.  1st draft will appear in a quarter time-frame.

Summary  Still need to build good model for ICSI first. (Arthur/Ziad/Moss) Training is also critical to understand why s2> s3.3.  Better everything for the decoder Arthur/Jahanzeb -> 50/50  Others : always on my “ priority queue ”, will pop up at the right time.