Publication Details
Title: When a Mismatch Can Be Good: Large Vocabulary Speech Recognition Trained with Idealized Tandem Features
Author: A. Faria and N. Morgan
Group: Speech
Date: March 2008
PDF: http://www.icsi.berkeley.edu/pubs/speech/faria2008wmc.pdf
Acknowledgements:
This work was partially supported by funding provided to ICSI by the U.S. Defense Advanced Research Projects Agency (DARPA). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of DARPA or of the U.S. Government.
Bibliographic Information:
Proceedings of the ACM Symposium on Applied Computing, Fortaleza, Brazil, pp. 1574-1577
Bibliographic Reference:
A. Faria and N. Morgan. When a Mismatch Can Be Good: Large Vocabulary Speech Recognition Trained with Idealized Tandem Features. Proceedings of the ACM Symposium on Applied Computing, Fortaleza, Brazil, pp. 1574-1577, March 2008
Author: A. Faria and N. Morgan
Group: Speech
Date: March 2008
PDF: http://www.icsi.berkeley.edu/pubs/speech/faria2008wmc.pdf
Acknowledgements:
This work was partially supported by funding provided to ICSI by the U.S. Defense Advanced Research Projects Agency (DARPA). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of DARPA or of the U.S. Government.
Bibliographic Information:
Proceedings of the ACM Symposium on Applied Computing, Fortaleza, Brazil, pp. 1574-1577
Bibliographic Reference:
A. Faria and N. Morgan. When a Mismatch Can Be Good: Large Vocabulary Speech Recognition Trained with Idealized Tandem Features. Proceedings of the ACM Symposium on Applied Computing, Fortaleza, Brazil, pp. 1574-1577, March 2008