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The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
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Claims 1-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,249,321. Although the claims at issue are not identical, they are not patentably distinct from each other because they are obvious variant of each other.
Instant application 19/029,691
Claim 1: A method implemented using one or more processors, comprising:
US Patent 12,249,321
Claim 1: A method implemented using one or more processors, comprising:
executing an automated assistant in an inactive listening state at least in part on a computing device operated by one or more users;
executing an automated assistant in an inactive listening state at least in part on a computing device operated by a user;
while in the inactive listening state, and prior to detecting one or more hot words that trigger transition of the automated assistant from the inactive listening state into an active listening state:
while in the inactive listening state, and prior to detecting one or more hot words that trigger transition of the automated assistant from the inactive listening state into an active listening state:
capturing, at one or more microphones, and temporarily storing in a memory buffer, as a first pre-event input stream, first audio data representing a first utterance spoken by one or more of the users;
capturing, at a microphone of the computing device operated by the user, and temporarily storing in a memory buffer of the computing device operated by the user, as a pre-event input stream, first audio data representing a first utterance spoken by the user;
capturing, at one or more of the microphones, and temporarily storing in the memory buffer, as a second pre-event input stream, second audio data representing a second utterance spoken by one or more of the users;
capturing, at the microphone as a post-event input stream, second audio data containing a third utterance spoken by the user after the second utterance;
detecting the one or more hot words in a third utterance spoken by one or more of the users after the first and second utterances;
after detecting the one or more hot words in the second utterance: capturing, at the microphone as a post-event input stream, second audio data containing a third utterance spoken by the user after the second utterance;
after detecting the one or more hot words in the third utterance:
after detecting the one or more hot words in the second utterance:
determining respective measures of fitness of the first and second pre-event input streams for triggering responsive action by the automated assistant;
determining respective measures of fitness of the pre-event and post-event input streams for triggering responsive action by the automated assistant;
based on the respective measures of fitness, selecting an input stream from a set of the first and second pre-event input streams for fulfillment by the automated assistant; and
based on the respective measures of fitness, selecting an input stream from a set of the pre-event input stream and the post-event input stream for fulfillment by the automated assistant; and
causing the automated assistant to perform one or more responsive actions based on a command associated with the selected input stream.
causing the automated assistant to perform one or more responsive actions based on a command associated with the selected input stream.
Claim 2: The method of claim 1,
Claim 2: The method of claim 1,
further comprising performing speaker recognition processing on at least a portion of the sound captured by the microphone to determine an identity of the user, wherein the respective measures of fitness are determined further based on the speaker recognition.
further comprising performing speaker recognition processing on at least a portion of the sound captured by the microphone to determine an identity of the user, wherein the respective measures of fitness are determined further based on the speaker recognition.
Claim 3: The method of claim 2,
Claim 3: The method of claim 2,
wherein the respective measures of fitness are determined based on the identity of the user matching an owner of the computing device.
wherein the respective measures of fitness are determined based on the identity of the user matching an owner of the computing device.
Claim 4: The method of claim 1,
Claim 4: The method of claim 1,
wherein the respective measures of fitness are determined based on respective similarity measures between the first and second pre-event input streams and one or more known command syntaxes.
wherein the respective measures of fitness are determined based on respective similarity measures between the pre-event and post-event input streams and one or more known command syntaxes.
Claim 5: The method of claim 1,
Claim 5: The method of claim 1,
wherein determining the respective measures of fitness includes analyzing one or more features of the user's voice in one or both of the first and second pre-event input streams.
wherein determining the respective measures of fitness includes analyzing one or more features of the user's voice in one or both of the pre-event and post-event input streams.
Claim 6: The method of claim 5,
Claim 6: The method of claim 5,
wherein the analyzing includes comparing the one or features of the user's voice to one or more voice features observed from utterances containing commands for automated assistants.
wherein the analyzing includes comparing the one or more features of the user's voice to one or more voice features observed from utterances containing commands for automated assistants.
Claim 7: The method of claim 5,
Claim 7: The method of claim 5,
wherein the analyzing includes applying the one or features of the user's voice as input across a machine learning model, wherein the machine learning model is trained to generate output indicative of whether the input is directed to an automated assistant.
wherein the analyzing includes applying the one or more features of the user's voice as input across a machine learning model, wherein the machine learning model is trained to generate output indicative of whether the input is directed to an automated assistant.
Claim 8: The method of claim 1,
Claim 8: The method of claim 1,
wherein one or more of the responsive actions comprises formulating, and submitting to a search engine, a search query that contains one or more tokens from the selected input stream; and
wherein one or more of the responsive actions comprises: formulating, and submitting to a search engine, a search query that contains one or more tokens from the selected input stream; and
providing output that conveys content responsive to the search query.
providing output that conveys content responsive to the search query.
Claim 9: The method of claim 1,
Claim 9: The method of claim 1,
wherein one or more of the responsive actions comprises operating a smart appliance.
wherein one or more of the responsive actions comprises operating a smart appliance.
Claim 10 (similarly Claim 19): A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:
Claim 10 (similarly Claim 19): A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:
execute an automated assistant in an inactive listening state at least in part on a computing device operated by one or more users;
execute an automated assistant in an inactive listening state at least in part on a computing device operated by a user;
while in the inactive listening state, and prior to detecting one or more hot words that trigger transition of the automated assistant from the inactive listening state into an active listening state:
while in the inactive listening state, and prior to one or more hot words being detected that trigger transition of the automated assistant from the inactive listening state into an active listening state:
capture, at one or more microphones, and temporarily storing in a memory buffer, as a first pre-event input stream, first audio data representing a first utterance spoken by one or more of the users;
capture, at a microphone of the computing device operated by the user, and temporarily storing in a memory buffer of the computing device operated by the user, as a pre-event input stream, first audio data representing a first utterance spoken by the user;
capture, at one or more of the microphones, and temporarily storing in the memory buffer, as a second pre-event input stream, second audio data representing a second utterance spoken by one or more of the users;
capture, at the microphone as a post-event input stream, second audio data containing a third utterance spoken by the user after the second utterance;
detect the one or more hot words in a third utterance spoken by one or more of the users after the first and second utterances;
after the one or more hot words are detected in the second utterance: capture, at the microphone as a post-event input stream, second audio data containing a third utterance spoken by the user after the second utterance;
after the one or more hot words are detected in the third utterance:
after the one or more hot words are detected in the second utterance:
determine respective measures of fitness of the first and second pre-event input streams for triggering responsive action by the automated assistant;
determine respective measures of fitness of the pre-event and post-event input streams for triggering responsive action by the automated assistant;
based on the respective measures of fitness, select an input stream from a set of the first and second pre-event input streams for fulfillment by the automated assistant; and
based on the respective measures of fitness, select an input stream from a set of the pre-event input stream and the post-event input stream for fulfillment by the automated assistant; and
cause the automated assistant to perform one or more responsive actions based on a command associated with the selected input stream.
cause the automated assistant to perform one or more responsive actions based on a command associated with the selected input stream.
Claim 11 (similarly Claim 20): The system of claim 10,
Claim 11 (similarly Claim 20): The system of claim 10,
further comprising instructions to perform speaker recognition processing on at least a portion of the sound captured by the microphone to determine an identity of the user, wherein the respective measures of fitness are determined further based on the speaker recognition.
further comprising instructions to perform speaker recognition processing on at least a portion of the sound captured by the microphone to determine an identity of the user, wherein the respective measures of fitness are determined further based on the speaker recognition.
Claim 12: The system of claim 11,
Claim 12: The system of claim 11,
wherein the respective measures of fitness are determined based on the identity of the user matching an owner of the computing device.
wherein the respective measures of fitness are determined based on the identity of the user matching an owner of the computing device.
Claim 13: The system of claim 10,
Claim 13: The system of claim 10,
wherein the respective measures of fitness are determined based on respective similarity measures between the first and second pre-event input streams and one or more known command syntaxes.
wherein the respective measures of fitness are determined based on respective similarity measures between the pre-event and post-event input streams and one or more known command syntaxes.
Claim 14: The system of claim 10,
Claim 14: The system of claim 10,
wherein the instructions to determine the respective measures of fitness include instructions to analyze one or more features of the user's voice in one or both of the first and second pre-event input streams.
wherein the instructions to determine the respective measures of fitness include instructions to analyze one or more features of the user's voice in one or both of the pre-event and post-event input streams.
Claim 15: The system of claim 14,
Claim 15: The system of claim 14,
wherein the instructions to analyze include instructions to compare the one or features of the user's voice to one or more voice features observed from utterances containing commands for automated assistants.
wherein the instructions to analyze include instructions to compare the one or more features of the user's voice to one or more voice features observed from utterances containing commands for automated assistants.
Claim 16: The system of claim 14,
Claim 16: The system of claim 14,
wherein the instructions to analyze include instructions to apply the one or features of the user's voice as input across a machine learning model, wherein the machine learning model is trained to generate output indicative of whether the input is directed to an automated assistant.
wherein the instructions to analyze include instructions to apply the one or more features of the user's voice as input across a machine learning model, wherein the machine learning model is trained to generate output indicative of whether the input is directed to an automated assistant.
Claim 17: The system of claim 10,
Claim 17: The system of claim 10,
wherein one or more of the responsive actions comprises: formulating, and submitting to a search engine, a search query that contains one or more tokens from the selected input stream; and causing output to be provided that conveys content responsive to the search query.
wherein one or more of the responsive actions comprises: formulation, and submission to a search engine, of a search query that contains one or more tokens from the selected input stream; and provision of output that conveys content responsive to the search query.
Claim 18: The system of claim 10,
Claim 18: The system of claim 10,
wherein one or more of the responsive actions comprises operating a smart appliance.
wherein one or more of the responsive actions comprises operation of a smart appliance.
Conclusion
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/IBRAHIM SIDDO/Primary Examiner, Art Unit 2681
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