Spoken dialog system using a best-fit language model and best-fit grammar
First Claim
1. A spoken dialog system using a best-fit language model, comprising:
- a dialog manager, coupled to a language model selector, that provides to the language model selector a current dialog state;
the language model selector, coupled to a plurality of dialog-state dependent language models, that selects one of the plurality of dialog-state dependent language models;
the plurality of dialog-state dependent language models that are interpolated from a general-task language model;
a large vocabulary continuous speech recognizer, coupled to the dialog manager and the language model selector, that receives input speech and generates a first hypothesis result for the input speech with a likelihood score, based on the selected dialog-state dependent language model;
the general-task language model, coupled to the large vocabulary continuous speech recognizer, that enables the large vocabulary continuous speech recognizer to generate a second hypothesis with a second likelihood score; and
a plurality of dialog strategies based on the language model system, coupled to the dialog manager.
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Abstract
A spoken dialog system using a best-fit language model and a spoken dialog system using best-fit grammar are disclosed. A spoken dialog system implementing both a best-fit language model and best-fit grammar is further disclosed. Regarding the language model, likelihood scores from a large vocabulary continuous speech recognition (“LVCSR”) module are used to select the best-fit language model among a general task language model and dialog-state dependent language models. Based on the chosen language model, a dialog manager can implement different strategies to improve general dialog performance and recognition accuracy. Regarding grammar, the best-fit grammar method improves performance and user experience of dialog systems by choosing the best-fit grammar among a general purpose grammar and dialog-state dependent sub-grammars. Based on the selected grammar pattern, the dialog system can choose from varying dialog strategies, resulting in an increase in user acceptance of spoken dialog systems.
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Citations
39 Claims
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1. A spoken dialog system using a best-fit language model, comprising:
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a dialog manager, coupled to a language model selector, that provides to the language model selector a current dialog state;
the language model selector, coupled to a plurality of dialog-state dependent language models, that selects one of the plurality of dialog-state dependent language models;
the plurality of dialog-state dependent language models that are interpolated from a general-task language model;
a large vocabulary continuous speech recognizer, coupled to the dialog manager and the language model selector, that receives input speech and generates a first hypothesis result for the input speech with a likelihood score, based on the selected dialog-state dependent language model;
the general-task language model, coupled to the large vocabulary continuous speech recognizer, that enables the large vocabulary continuous speech recognizer to generate a second hypothesis with a second likelihood score; and
a plurality of dialog strategies based on the language model system, coupled to the dialog manager. - View Dependent Claims (2, 3, 4)
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5. A spoken dialog system using best-fit grammar, comprising:
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a dialog manager, coupled to a grammar selector, that provides to the grammar selector a current dialog state;
the grammar selector, coupled to a plurality of dialog-state dependent sub-grammars, that selects one of the plurality of dialog-state dependent sub-grammars;
the plurality of dialog-state dependent sub-grammars, that contain a plurality of speech patterns;
a speech recognition module, coupled to the dialog manager and the grammar selector, that receives input speech;
a general-purpose grammar, coupled to the grammar selector, that contains patterns of general user responses; and
a plurality of dialog strategies based on the selected grammar system, coupled to the dialog manager, to enhance dialog performance. - View Dependent Claims (6, 7, 8, 9, 10)
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11. A spoken dialog system implementing a best-fit language model, comprising a computer readable medium and a computer readable program code stored on the computer readable medium having instructions to:
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receive a current dialog state from a dialog manager;
select a dialog-state dependent language model from a plurality of dialog-state dependent language models based on the current dialog state;
generate a first hypothesis result for input speech with a first likelihood score;
generate a second hypothesis result for input speech with a second likelihood score;
select a best-fit language model from the higher value of the first likelihood score and the second likelihood score; and
implement dialog strategies, based on the best-fit language model, to improve dialog performance. - View Dependent Claims (12, 13, 14, 15)
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16. A spoken dialog system implementing best-fit grammar, comprising a computer readable medium and a computer readable program code stored on the computer readable medium having instructions to:
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receive a current dialog state from a dialog manager;
select one of a plurality of dialog-state dependent sub-grammars based on the current dialog state;
select a general-purpose grammar, if the chosen dialog-state dependent sub-grammar fails to provide a matching pattern of input speech; and
implement dialog strategies, based on one of the dialog-state dependent sub-grammar and the general-purpose grammar, to improve dialog performance. - View Dependent Claims (17, 18, 19, 20)
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21. A method of implementing a best-fit language model in a spoken dialog system, comprising:
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receiving a current dialog state from a dialog manager;
choosing a dialog-state dependent language model from a plurality of dialog-state dependent language models based on the current dialog state;
calculating a first hypothesis result for input speech with a first likelihood score;
calculating a second hypothesis result for input speech with a second likelihood score;
choosing a best-fit language model from the higher value of the first likelihood score and the second likelihood score; and
deploying dialog strategies, based on the best-fit language model, to improve dialog performance. - View Dependent Claims (22, 23, 24)
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25. A method of implementing a best-fit grammar model in a spoken dialog system, comprising:
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receiving a current dialog state from a dialog manager;
choosing one of a plurality of dialog-state dependent sub-grammars based on the current dialog state;
choosing a general-purpose grammar, if the chosen dialog-state dependent sub-grammar fails to provide a matching pattern of input speech; and
employing dialog strategies, based on one of the dialog-state dependent sub-grammar and the general-purpose grammar, to improve dialog performance. - View Dependent Claims (26, 27, 28)
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29. A spoken dialog system using a best-fit language model and best-fit grammar, comprising:
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a dialog manager, coupled to a language model selector and a grammar selector, that provides to the language model selector and to the grammar selector a current dialog state;
the language model selector, coupled to a plurality of dialog-state dependent language models, that selects one of the plurality of dialog-state dependent language models;
the grammar selector, coupled to a plurality of dialog-state dependent sub-grammars, that contain a plurality of speech patterns;
the plurality of dialog-state dependent language models that are interpolated from a general-task language model;
the plurality of dialog-state dependent sub-grammars that contain a plurality of speech patterns;
a large vocabulary continuous speech recognizer, coupled to the dialog manager and the language model selector and a language understanding module, that receives input speech and generates a first hypothesis result for the input speech with a likelihood score, based on the selected dialog-state dependent language model;
the language understanding module, coupled to the dialog manager and to the grammar selector and to large vocabulary continuous speech recognizer, that extracts critical information from a word sequence generated by the large vocabulary continuous speech recognizer;
the general-task language model, coupled to the large vocabulary continuous speech recognizer, that enables the large vocabulary continuous speech recognizer to generate a second hypothesis with a second likelihood score;
a general-purpose grammar, coupled to the grammar selector, that contains patterns of general user responses; and
a plurality of dialog strategies based on the language model system and a plurality of dialog strategies based on the selected grammar system, coupled to the dialog manager. - View Dependent Claims (30, 31)
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32. A spoken dialog system implementing a best-fit language model and best-fit grammar, comprising a computer readable medium and a computer readable program code stored on the computer readable medium having instructions to:
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receive a current dialog state from a dialog manager;
select a dialog-state dependent language model from a plurality of dialog-state dependent language models based on the current dialog state;
select a dialog-state dependent sub-grammar from a plurality of dialog-state dependent sub-grammars based on the current dialog state;
select a general-purpose grammar, if the chosen dialog-state dependent sub-grammar fails to provide a matching pattern of input speech;
generate a first hypothesis result for input speech with a first likelihood score;
generate a second hypothesis result for input speech with a second likelihood score;
select a best-fit language model from the higher value of the first likelihood score and the second likelihood score; and
implement dialog strategies, based on the best-fit language model and based on one of the dialog-state dependent sub-grammar and the general-purpose grammar. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39)
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Specification