SYSTEM AND METHOD FOR RECOGNIZING A USER VOICE COMMAND IN NOISY ENVIRONMENT
First Claim
1. An automatic speech recognition system for recognizing a user voice command in noisy environment, comprising:
- matching means for matching elements retrieved from speech units forming said command with templates in a template library library;
processing means including a MultiLayer Perceptron for computing posterior templates (P(Otemplate(q))) stored as said templates in said template library;
means for retrieving posterior vectors (P(Otest(q))) from said speech units, said posterior vectors being used as said elements;
calculating means for automatically selecting posterior templates stored in said template library, wherein said calculating means use a graph approach, such as the Gabriel'"'"'s approach, or the relative neighbour approach, or a linear interpolation to prepare posterior templates from training templates.
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Abstract
An automatic speech recognition system for recognizing a user voice command in noisy environment, including: matching means for matching elements retrieved from speech units forming said command with templates in a template library; characterized by processing means including a MultiLayer Perceptron for computing posterior templates (P(Otemplate(q))) stored as said templates in said template library; means for retrieving posterior vectors (P(Otest(q))) from said speech units, said posterior vectors being used as said elements. The present invention relates also to a method for recognizing a user voice command in noisy environments.
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Citations
19 Claims
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1. An automatic speech recognition system for recognizing a user voice command in noisy environment, comprising:
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matching means for matching elements retrieved from speech units forming said command with templates in a template library library; processing means including a MultiLayer Perceptron for computing posterior templates (P(Otemplate(q))) stored as said templates in said template library; means for retrieving posterior vectors (P(Otest(q))) from said speech units, said posterior vectors being used as said elements; calculating means for automatically selecting posterior templates stored in said template library, wherein said calculating means use a graph approach, such as the Gabriel'"'"'s approach, or the relative neighbour approach, or a linear interpolation to prepare posterior templates from training templates. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. An automatic speech recognition method of recognizing a voice command spoken by a user in a noisy environment, said method comprising:
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matching elements retrieved from speech units forming said command with templates in a template library; determining a sequence of templates that minimizes the distance between said elements and said templates; wherein said templates are posterior templates (P(Otemplate(q))) and said elements retrieved from speech units are posterior vectors (P(Otest(q))); said posterior templates and said posterior vectors being generated with at least one MultiLayer Perceptron; wherein it includes a step for selecting said posterior templates from training templates, said step comprising; determination of Gabriel/relative neighbours by calculating a matrix of distances between all said training template, visiting each training template, marking a training template if all its neighbours are of the same class as the current training template, deleting all marked training templates. - View Dependent Claims (17, 18, 19)
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Specification