System and method for spelling recognition using speech and non-speech input
First Claim
1. A method for recognizing a combination of speech and alternate input, the method comprising:
- receiving a non-speech input from a user;
dynamically constructing an unweighted grammar permitting all letter sequences that map to the received non-speech input;
keypad constraints constructing a weighted grammar using the unweighted grammar and a statistical letter model trained on domain data;
receiving speech from the user associated with the non-speech input; and
recognizing the received speech and non-speech input using the constructed weighted grammar.
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Accused Products
Abstract
A system and method for non-speech input or keypad-aided word and spelling recognition is disclosed. The method comprises performing spelling recognition via automatic speech recognition (ASR) on received speech from a user, the ASR being performed using a statistical letter model trained on domain data and producing a letter lattice RLN. If an ASR confidence is below a predetermined level, then the method comprises receiving non-speech input from the user, generating a keypad constraint grammar K and generating a letter string based on a composition of finite state transducers RLN and K. Other variations of the invention include recognizing input by first receiving non-speech input, dynamically generating an unweighted grammar, generating a weighted grammar using domain data, and then performing speech, and thus spelling, recognition on input speech using the weighted grammar.
39 Citations
23 Claims
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1. A method for recognizing a combination of speech and alternate input, the method comprising:
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receiving a non-speech input from a user;
dynamically constructing an unweighted grammar permitting all letter sequences that map to the received non-speech input;
keypad constraintsconstructing a weighted grammar using the unweighted grammar and a statistical letter model trained on domain data;
receiving speech from the user associated with the non-speech input; and
recognizing the received speech and non-speech input using the constructed weighted grammar. - View Dependent Claims (2, 3, 4, 5, 6, 7, 16)
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8. A method of recognizing input from a user, the method comprising:
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performing spelling recognition via automatic speech recognition (ASR) on received speech from a user, the ASR being performed using a statistical letter model trained on domain data and producing a letter lattice RLN;
if an ASR confidence is below a predetermined level, then;
receiving non-speech input from the user;
generating a non-speech constraint grammar K; and
generating a letter string based on a composition of RLN and K. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 17, 18)
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19. A system for recognizing a combination of speech and alternate input, the system comprising:
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means for receiving a non-speech input from a user;
means for dynamically constructing an unweighted grammar permitting all letter sequences that map to the received non-speech input;
keypad constraintsmeans for constructing a weighted grammar using the unweighted grammar and a statistical letter model trained on domain data;
means for receiving speech from the user associated with the non-speech input; and
means for recognizing the received speech and non-speech input using the constructed weighted grammar.
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20. A system for recognizing input from a user, the system comprising:
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means for performing spelling recognition via automatic speech recognition (ASR) on received speech from a user, the ASR being performed using a statistical letter model trained on domain data and producing a letter lattice RLN;
if an ASR confidence is below a predetermined level, then the means for performing spelling recognition further;
receives non-speech input from the user;
generates a non-speech constraint grammar K; and
generates a letter string based on a composition of RLN and K.
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22. A computer-readable medium storing instructions for controlling a computing device to recognize a combination of speech and non-speech input, the instructions comprising:
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receiving a non-speech input from a user;
dynamically constructing an unweighted grammar permitting all letter sequences that map to the received non-speech input;
keypad constraintsconstructing a weighted grammar using the unweighted grammar and a statistical letter model trained on domain data;
receiving speech from the user associated with the non-speech input; and
recognizing the received speech and non-speech input using the constructed weighted grammar.
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23. A computer-readable medium storing instructions for controlling a computing device to recognize input from a user, the instructions comprising:
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performing spelling recognition via automatic speech recognition (ASR) on received speech from a user, the ASR being performed using a statistical letter model trained on domain data and producing a letter lattice RLN;
if an ASR confidence is below a predetermined level, then;
receiving non-speech input from the user;
generating a non-speech constraint grammar K; and
generating a letter string based on a composition of RLN, and K.
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Specification