IEEE  TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING
Special Issue on New Frontiers in Rich Transcription

A rich transcript is a transcript of a recorded event along with
metadata to enrich the word stream with useful information such as
identifying speakers, sentence units, proper nouns, speaker locations,
etc. As the volume of online media increases and additional, layered
content extraction technologies are built, rich transcription has
become a critical foundation for delivering extracted content to
down-stream applications such as spoken document retrieval,
summarization, semantic navigation, speech data mining, and others.

The special issue on 'New Frontiers in Rich Transcription' will focus
on the recent research on technologies that generate rich
transcriptions automatically and on its applications. The field of
rich transcription draws on expertise from a variety of disciplines
including: (a) signal acquistion (recording room design, microphone
and camera design, sensor synchronization, etc.), (b) automatic
content extraction and supporting technologies (signal processing,
room acoustics compensation, spatial and multichannel audio
processing, robust speech recognition, speaker
recognition/diarization/tracking, spoken language understanding,
speech recognition, multimodal information integration from audio and
video sensors,  etc.), (c) corpora infrastructure (meta-data
standards, annotations  procedures, etc.), and (d) performance
benchmarking (ground truthing, evaluation metrics, etc.) In the end,
rich transcriptions serve as enabler of a variety of spoken document
applications.

Many large international projects (e.g. the NIST RT evaluations) have
been active in the area of rich transcription, engaging in efforts of
extracting useful content from a range of media such as broadcast
news, conversational telephone speech, multi-party meeting recordings,
lecture recordings. The current special issue aims to be one of the
first in bringing together the enabling technologies that are critical
in rich transcription of media with a large variety of speaker styles,
spoken content and acoustic environments. This area has also led to
new research directions recently, such as multimodal signal processing
or automatic human behavior modeling.

The purpose of this special issue is to present overview papers,
recent advances in Rich Transcription research as well as new ideas
for the direction of the field.  We encourage submissions about the
following and other related topics:
  * Robust Automatic Speech Recognition for Rich Transcription
  * Speaker Diarization and Localization
  * Speaker-attributed-Speech-to-Text
  * Data collection and Annotation
  * Benchmarking Metrology for Rich Transcription
  * Natural language processing for Rich Transcription
  * Multimodal Processing for Rich Transcription
  * Online Methods for Rich Transcription
  * Future Trends in Rich Transcription

Submissions must not have been previously published, with the
exception that substantial extensions of conference papers are
considered.

Submissions must be made through IEEE's manuscript central at:
http://mc.manuscriptcentral.com/sps-ieee
Selecting the special issue as target.

Important Dates:
EXTENDED Submission deadline: 1 September 2010
Notification of acceptance: 1 January 2011
Final manuscript due:  1 July 2011

For further information, please contact the guest editors:
Gerald Friedland, fractor@icsi.berkeley.edu
Jonathan Fiscus, jfiscus@nist.gov
Thomas Hain, T.Hain@dcs.shef.ac.uk
Sadaoki Furui, furui@cs.titech.ac.jp