US6021387A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Speech recognition apparatus for consumer electronic applications
Assignee: Sensory Circuits Inc
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Filing: 1998-02-23
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Granted: 2000-02-01
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Expires: 2018-02-23
Abstract
Abstract A spoken word or phrase recognition device. The device does not require a digital signal processor, large RAM, or extensive analog circuitry. The input audio signal is digitized and passed recursively through a digital difference filter to produce a multiplicity of filtered output waveforms. These waveforms are processed in real time by a microprocessor to generate a pattern that is recognized by a neural network pattern classifier that operates in software in the microprocessor. By application of additional techniques, this device has been shown to recognize an unknown speaker saying a digit from zero through nine with an accuracy greater than 99%. Because of the recognition accuracy and cost-effective design, the device may be used in cost sensitive applications such as toys, electronic learning aids, and consumer electronic products.
Inventors
- 👤 Forrest S. Mozer
- 👤 Michael C. Mozer
- 👤 Todd F. Mozer
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-03 01:10
CPC Classifications
G; G10; G10L; G10L15/00; G10L15/08; G10L15/16
Claims Analysis
Total Claims: 9
Claim 1
Independent Claim
97 words
A neural network for classifying sampled signals into a plurality of classes comprising: a representation transformer that accepts samples of a selected signal as input, applies a transformation to the input signal to transform the input signal into a representational space, and outputs a transformed signal, wherein the transformation distributes sampled signals belonging to a given class within the representational space in accordance with a predetermined distribution associated with the given class; and a Bayes classifier that accepts the transformed signal as an input and assigns the input signal to a class with the highest posterior probability.
Claim 2
Dependent Claim
97 words
A neural network for classifying sampled signals into a plurality of classes comprising: a representation transformer that accepts samples of a selected signal as input, applies a transformation to the input signal to transform the input signal into a representational space, and outputs a transformed signal, wherein the transformation distributes sampled signals belonging to a given class within the representational space in accordance with a predetermined distribution associated with the given class; and a Bayes classifier that accepts the transformed signal as an input and assigns the input signal to a class with the highest posterior probability.
Claim 3
Dependent Claim
24 words
The neural network of claim 1 wherein the predetermined distribution for at least one of the plurality of classes is a multivariate Gaussian distribution.
Claim 4
Dependent Claim
24 words
The neural network of claim 1 wherein the predetermined distribution for at least one of said plurality of classes is a multivariate beta distribution.
Claim 5
Dependent Claim
19 words
The neural network of claim 1 wherein the predetermined distribution has a covariance matrix that is a diagonal matrix.
Claim 6
Dependent Claim
32 words
The neural network of claim 1 wherein weights of the neural network and parameters of a predetermined distribution associated with one of the plurality of classes are obtained by an optimization procedure.
Claim 7
Dependent Claim
16 words
The neural network of claim 5 wherein the optimization procedure is a method of steepest descent.
Claim 8
Dependent Claim
19 words
The neural network of claim 1 wherein the mean of each predetermined distribution associated with a class is adjustable.
Claim 9
Dependent Claim
19 words
The neural network of claim 1 wherein said Bayes classifier accepts prior probabilities for each class as an input.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2003-01-31 | 2003-08-02 | 2004-02-01 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2007-01-31 | 2007-08-02 | 2008-02-01 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2011-01-31 | 2011-08-02 | 2012-02-01 | $7700.00 | Window Closed / Lapsed |