SPINE: Speech in Noisy Environments
Ramana Rao Gadde
SRI participated regularly in the evaluations of speech recognition
systems on speech collected under noisy conditions.
The SPINE task was sponsored by DARPA.
SRI's SPINE recognition systems is based on the DECIPHER recognizer
and builds on the research carried out under the
Consistency Modeling and
One of our research projects, funded by DARPA's
Reliable Omni-Present Automatic Recognition (ROAR) program,
involves the use of multiple sensors for
robustness in noisy environments.
Another line of research under this program explores approach to
dialog modeling without large amounts of labeled training data.
Publications and Presentations
- V.R.R. Gadde & A. Stolcke, The SRI Spine
2000 Evaluation System,
Evaluation of Speech Technology in Noisy Environments Workshop,
Naval Research Laboratory, Washington, DC, 10-11 October 2000.
- V.R.R. Gadde, A. Stolcke, D. Vergyri, J. Zheng, K. Sonmez, &
SRI 2001 SPINE Evaluation
System, Presentation at the DARPA SPINE Workshop, Orlando, FL,
Nov. 29, 2001.
H. Franco, M. Graciarena, K. Sonmez, & H. Bratt,
Combining Heterogeneous Sensors with
Standard Microphones for Noise Robust Recognition,
Presentation at the DARPA ROAR Workshop, Orlando, FL,
Nov. 30, 2001.
V. R. Rao Gadde, A. Stolcke, D. Vergyri, J. Zheng, K. Sonmez, and
A. Venkataraman (2002),
Building an ASR System for Noisy Environments:
SRI's 2001 SPINE Evaluation System.
Proc. Intl. Conf. on Spoken Language Processing, Denver,
vol. 3, pp. 1577-1580.
A. Venkataraman, A. Stolcke, & E. Shriberg (2002),
Automatic Dialog Act Tagging with Minimal Supervision.
Proc. 9th Australian International Conference on Speech Science
and Technology, Melbourne.
A. Venkataraman, L. Ferrer, A. Stolcke, & E. Shriberg (2003),
Training a Prosody-based Dialog Act Tagger from Unlabeled Data.
To appear in
Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing,