Speech processing using maximum likelihood continuity mapping
Abstract
Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.
- Inventors:
-
- Santa Fe, NM
- Issue Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- OSTI Identifier:
- 872961
- Patent Number(s):
- 6052662
- Assignee:
- Regents of University of California (Los Alamos, MX)
- Patent Classifications (CPCs):
-
G - PHYSICS G10 - MUSICAL INSTRUMENTS G10L - SPEECH ANALYSIS OR SYNTHESIS
- DOE Contract Number:
- W-7405-ENG-36
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- speech; processing; maximum; likelihood; continuity; mapping; obtained; probabilistic; static; sounds; pseudo-articulator; positions; allows; sequences; mapped; smooth; addition; method; learning; position; described; set; training; data; composed; applied; various; analysis; tasks; including; recognition; speaker; coding; synthesis; voice; mimicry; speech sounds; speech processing; speech coding; training data; /704/
Citation Formats
Hogden, John E. Speech processing using maximum likelihood continuity mapping. United States: N. p., 2000.
Web.
Hogden, John E. Speech processing using maximum likelihood continuity mapping. United States.
Hogden, John E. Sat .
"Speech processing using maximum likelihood continuity mapping". United States. https://www.osti.gov/servlets/purl/872961.
@article{osti_872961,
title = {Speech processing using maximum likelihood continuity mapping},
author = {Hogden, John E},
abstractNote = {Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2000},
month = {Sat Jan 01 00:00:00 EST 2000}
}
Works referenced in this record:
Techniques for estimating vocal-tract shapes from the speech signal
journal, January 1994
- Schroeter, J.; Sondhi, Man Mohan
- IEEE Transactions on Speech and Audio Processing, Vol. 2, Issue 1, p. 133-150
Accurate recovery of articulator positions from acoustics: New conclusions based on human data
journal, September 1996
- Hogden, John; Lofqvist, Anders; Gracco, Vince
- The Journal of the Acoustical Society of America, Vol. 100, Issue 3
Electromagnetic midsagittal articulometer systems for transducing speech articulatory movements
journal, December 1992
- Perkell, Joseph S.; Cohen, Marc H.; Svirsky, Mario A.
- The Journal of the Acoustical Society of America, Vol. 92, Issue 6
A statistical approach to automatic speech recognition using the atomic speech units constructed from overlapping articulatory features
journal, May 1994
- Deng, Li; Sun, Don X.
- The Journal of the Acoustical Society of America, Vol. 95, Issue 5
On automatic estimation of articulatory parameters in a text-to-speech system
journal, January 1992
- Parthasarathy, S.; Coker, Cecil H.
- Computer Speech & Language, Vol. 6, Issue 1
Landmark detection for distinctive featureābased speech recognition
journal, November 1996
- Liu, Sharlene A.
- The Journal of the Acoustical Society of America, Vol. 100, Issue 5
The potential role of speech production models in automatic speech recognition
journal, March 1996
- Rose, R. C.; Schroeter, J.; Sondhi, M. M.
- The Journal of the Acoustical Society of America, Vol. 99, Issue 3
Adding articulatory features to acoustic features for automatic speech recognition
journal, May 1995
- Zlokarnik, Igor
- The Journal of the Acoustical Society of America, Vol. 97, Issue 5