Compilation of weighted finite-state transducers from decision trees
First Claim
1. An automated method for synthesizing speech sounds based on a finite-state representation of linguistic data generated based on one or more decision tree models of said linguistic data, each of the one or more decision tree models comprising one or more terminal nodes thereof, the method comprising the steps of:
- generating one or more weighted rewrite rules based on one or more of the terminal nodes of the one or more decision tree models;
generating one or more weighted finite-state transducers based on one or more of the one or more weighted rewrite rules; and
synthesizing one or more of said speech sounds based on said one or more weighted finite-state transducers.
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Abstract
A method for automatically converting a decision tree into one or more weighted finite-state transducers. Specifically, the method in accordance with an illustrative embodiment of the present invention processes one or more terminal (i.e., leaf) nodes of a given decision tree to generate one or more corresponding weighted rewrite rules. Then, these weighted rewrite rules are processed to generate weighted finite-state transducers corresponding to the one or more terminal nodes of the decision tree. In this manner, decision trees may be advantageously compiled into weighted finite-state transducers, and these transducers may then be used directly in various speech and natural language processing systems. The weighted rewrite rules employed herein comprise an extension of conventional rewrite rules, familiar to those skilled in the art.
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Citations
30 Claims
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1. An automated method for synthesizing speech sounds based on a finite-state representation of linguistic data generated based on one or more decision tree models of said linguistic data, each of the one or more decision tree models comprising one or more terminal nodes thereof, the method comprising the steps of:
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generating one or more weighted rewrite rules based on one or more of the terminal nodes of the one or more decision tree models; generating one or more weighted finite-state transducers based on one or more of the one or more weighted rewrite rules; and synthesizing one or more of said speech sounds based on said one or more weighted finite-state transducers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An apparatus for automatically generating a finite-state representation of linguistic data based on one or more decision tree models of said linguistic data, each of the one or more decision tree models comprising one or more terminal nodes thereof, the apparatus comprising:
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means for generating one or more weighted rewrite rules based on one or more of the terminal nodes of the one or more decision tree models; and means for generating one or more weighted finite-state transducers based on one or more of the one or more weighted rewrite rules. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. An automated method for recognizing speech sounds based on a finite-state representation of linguistic data generated based on one or more decision tree models of said linguistic data, each of the one or more decision tree models comprising one or more terminal nodes thereof, the method comprising the steps of:
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generating one or more weighted rewrite rules based on one or more of the terminal nodes of the one or more decision tree models; generating one or more weighted finite-state transducers based on one or more of the one or more weighted rewrite rules; and recognizing one or more of said speech sounds based on said one or more weighted finite-state transducers. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification