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Title: Time series association learning

An acoustic input is recognized from inferred articulatory movements output by a learned relationship between training acoustic waveforms and articulatory movements. The inferred movements are compared with template patterns prepared from training movements when the relationship was learned to regenerate an acoustic recognition. In a preferred embodiment, the acoustic articulatory relationships are learned by a neural network. Subsequent input acoustic patterns then generate the inferred articulatory movements for use with the templates. Articulatory movement data may be supplemented with characteristic acoustic information, e.g. relative power and high frequency data, to improve template recognition.
Inventors:
 [1]
  1. (Santa Fe, NM)
Issue Date:
OSTI Identifier:
870020
Assignee:
United States of America as represented by United States (Washington, DC) LANL
Patent Number(s):
US 5440661
Contract Number:
W-7405-ENG-36
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM
Country of Publication:
United States
Language:
English
Subject:
time; series; association; learning; acoustic; input; recognized; inferred; articulatory; movements; output; learned; relationship; training; waveforms; compared; template; patterns; prepared; regenerate; recognition; preferred; embodiment; relationships; neural; network; subsequent; generate; templates; movement; data; supplemented; characteristic; information; relative; power; frequency; improve; acoustic wave; neural network; preferred embodiment; time series; articulatory movements; neural net; /704/