Rejecting out-of-vocabulary words
First Claim
Patent Images
1. A computer-implemented method comprising:
- determining, based on applying an input gesture to a vocabulary of modeled training gestures;
a likelihood that the input gesture matches each modeled training gesture, anda modeled training gesture having a highest likelihood;
subsequent to determining the modeled training gesture having the highest likelihood, determining a quantity of states of the input gesture that match corresponding states of the modeled training gesture determined to have the highest likelihood, wherein each state of both the input gesture and the modeled training gesture comprises a portion of a gesture; and
rejecting, with a processor, the input gesture if the determined quantity of matching states does not satisfy a threshold, wherein the threshold expresses a quantity or percentage of the total quantity of the states of the input gesture.
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Abstract
Enhanced rejection of out-of-vocabulary words, in which, based on applying an input gesture to hidden Markov models collectively modeling a vocabulary of training gestures, a likelihood that the input gesture matches each training gesture, and a quantity of states of the input gesture that match corresponding states of a modeled training gesture determined to have a highest likelihood are determined. The input gesture is rejected if the determined quantity does not satisfy a threshold.
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Citations
24 Claims
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1. A computer-implemented method comprising:
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determining, based on applying an input gesture to a vocabulary of modeled training gestures; a likelihood that the input gesture matches each modeled training gesture, and a modeled training gesture having a highest likelihood; subsequent to determining the modeled training gesture having the highest likelihood, determining a quantity of states of the input gesture that match corresponding states of the modeled training gesture determined to have the highest likelihood, wherein each state of both the input gesture and the modeled training gesture comprises a portion of a gesture; and rejecting, with a processor, the input gesture if the determined quantity of matching states does not satisfy a threshold, wherein the threshold expresses a quantity or percentage of the total quantity of the states of the input gesture. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer-implemented method comprising:
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determining, based on applying an input gesture to a vocabulary of modeled training gestures; a likelihood that the input gesture matches each training gesture, and a quantity of states of the input gesture that match corresponding states of a modeled training gesture determined to have a highest likelihood; and rejecting, with a processor, the input gesture if the determined quantity does not satisfy a threshold; wherein determining the quantity of states of the input gesture that match corresponding states of the modeled training gesture determined to have the highest likelihood further comprises; determining the quantity of states for which an extracted median for the input gesture in each state is greater than or equal to a minimum of extracted medians in a corresponding state for a set of training samples of the modeled training gesture determined to have the highest likelihood. - View Dependent Claims (15)
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16. A device comprising a processor configured to:
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determine, based on applying an input gesture to a vocabulary of modeled training gestures; a likelihood that the input gesture matches each modeled training gesture, and a modeled training gesture having a highest likelihood; subsequent to determining the modeled training gesture having the highest likelihood, determine a quantity of states of the input gesture that match corresponding states of the modeled training gesture determined to have the highest likelihood, wherein each state of both the input gesture and the modeled training gesture comprises a portion of a gesture; and reject the input gesture if the determined quantity of matching states fails to satisfy a threshold, wherein the threshold expresses a quantity or percentage of the total quantity of the states of the input gesture. - View Dependent Claims (17, 18, 19)
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20. A non-transitory computer-readable medium encoded with a computer program comprising instructions that, when executed, operate to cause a computer to perform operations comprising:
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determining, based on applying an input gesture to a vocabulary of modeled training gestures; a likelihood that the input gesture matches each modeled training gesture, and a modeled training gesture having a highest likelihood; subsequent to determining the modeled training gesture having the highest likelihood, determining a quantity of states of the input gesture that match corresponding states of a modeled training gesture determined to have the highest likelihood, wherein each state of both the input gesture and the modeled training gesture comprises a portion of a gesture; and rejecting the input gesture if the determined quantity of matching states fails to satisfy a threshold, wherein the threshold expresses a quantity or percentage of the total quantity of the states of the input gesture.
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21. An apparatus comprising:
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means for determining, based on applying an input gesture to a vocabulary of modeled training gestures; a likelihood that the input gesture matches each modeled training gesture, and a modeled training gesture having a highest likelihood; means for determining, subsequent to determining the modeled training gesture having the highest likelihood, a quantity of states of the input gesture that match corresponding states of the modeled training gesture determined to have the highest likelihood, wherein each state of both the input gesture and the modeled training gesture comprises a portion of a gesture; and means for rejecting the input gesture if the determined quantity of matching states does not satisfy a threshold, wherein the threshold expresses a quantity or percentage of the total quantity of the states of the input gesture. - View Dependent Claims (22, 23, 24)
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Specification