DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04 September 2026 has been entered.
Response to Amendment
The amendment filed 04 September 2026 has been accepted and considered in this Office Action. Claims 1 and 11 have been amended. Examiner notes that some limitations have been removed without being indicated as removed by being crossed out. Specifically, “wherein the dialog history data is received as part of the transcription request from the user device” has been removed from claims 1 and 11.
Response to Arguments
Applicant's arguments filed 04 September 2026 regarding the limitations “wherein the dialog history data is received as part of the transcription request from the user device” have been fully considered but they are not persuasive. These limitations no longer appear in the claims, and thus these arguments are moot.
Applicant’s arguments with respect to claim(s) 1 and 11 and the limitations “wherein the current stage in the multi-stage voice activity is determined based on the prior stage indicated by the dialog history data” have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-3, 6-8, 11-13, and 16-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Epstein et al (US PAP 2005/0137868) in view of Bui et al. (US PAP 2017/0228366).
Consider claim 1, Epstein teaches a computer-implemented method executed on data processing hardware that causes the data processing hardware to perform operations (abstract) comprising:
during a current stage in a multi-stage voice activity corresponding to a series of user interactions between a user and an application executing on a user device associated with the user (0004, conversational speech systems, figures 2-4, system returns to prompt generation after recognition, indicating multi-turn dialog), receiving a transcription request for a voice input captured by the user device (i.e. figure 2, steps 250, and step 200, figure 3, steps 350, and step 300, steps 450, and step 400, system prompts, user speaks), the transcription request comprising:
audio data indicating the voice input (figure 2, steps 250, figure 3, steps 350, figure 4, steps 450, user speaks); and
dialog history data indicating a prior stage from the multi-stage voice activity (figure 2, steps 210, 220, figure 3, steps 310, 320, figure 4, steps 410, 420, 0044, prompt is provided to prompt analysis module to determine possible responses by the user);
providing, for input to a language model, a set of n-grams associated with the current stage in the multi-stage voice activity (0025, determining a set of n-grams associated with possible responses), the set of n-grams associated with the current stage in the multi-stage voice activity biasing the language model to increase probability scores indicated by the language model of n-grams in the set of n-grams (0041,43, 0047, 0050, boosting n-gram probabilities for words user is likely to say ); and
based on the dialog history data, processing, using the biased language model, the audio data to generate a transcription of the voice input (0041,43, 0047, 0050, boosting n-gram probabilities for words user is likely to say based on dialog prompt, i.e. history, and preforming recognition).
Epstein does not specifically teach dialog history data indicating a prior stage from the multi-stage voice activity that corresponds to a prior transcription request preceding the transcription request; and
wherein the current stage in the multi-stage voice activity is determined based on the prior stage indicated by the dialog history data.
In the same field of dialog systems, Bui teaches dialog history data indicating a prior stage from the multi-stage voice activity that corresponds to a prior transcription request preceding the transcription request (0060-61, dialog state history tracking, also see column 274 in figure 2B-D); and
wherein the current stage in the multi-stage voice activity is determined based on the prior stage indicated by the dialog history data (0057, current dialog state uses dialog history up until that point to determine current dialog state).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to use dialog history to determine dialog state as taught by Bui in the system of Epstein in order to improve the ability for the system to more accurately narrow down possible inputs by the user (Bui 0005).
Consider claim 2, Epstein teaches the computer-implemented method of claim 1, wherein each n-gram of the set of n-grams comprises a respective non-zero probability score (0041, n-grams determined form prompt can be interpolated with base n-gram model to boost scores, Thus, n-gram probabilities must be non-zero if resulting in a boost).
Consider claim 3, Epstein teaches the computer-implemented method of claim 2, wherein biasing the language model to increase the probability scores comprises biasing the language model by increasing the respective non-zero probability score for each n-gram of the set of n- grams associated with the current stage in the multi-stage voice activity. (0041, n-grams determined form prompt can be interpolated with base n-gram model to boost scores. Thus, n-gram probabilities must be non-zero if resulting in a boost).
Consider claim 5, Epstein and Bui teach the computer-implemented method of claim 1, Bui further teaches wherein the data processing hardware resides on a remote server in communication with the user device via a network (Figure 1, 0037-42, processing at a server device connected to user device).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to use a server as taught by Bui in in the system of Epstein and BUi in order to reduce the amount of processing that has to be performed by the user device.
Consider claim 6, Epstein teaches the computer-implemented method of claim 1, wherein the data processing hardware resides on the user device (0051, system may be solely implemented on a general-purpose computer).
Consider claim 7, Epstein teaches the computer-implemented method of claim 1, wherein the current stage in the multi-stage voice activity pertains to an application-specific task for the application (0020, selecting funds to trade, for example).
Consider claim 8, Epstein teaches the computer-implemented method of claim 1, wherein the language model comprises an n-gram language model (0021, n-gram LM).
Consider claim 9, Epstein and Bui teach the computer-implemented method of claim 1, Bui further teaches wherein the user device comprises a smart phone (0040, client device may be a smart phone).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to use a phone as taught by Bui in in the system of Epstein and Bui in order to increase convenience for the end user to user the system.
Consider claim 10, Epstein and Bui teach teach the computer-implemented method of claim 1. Bui further teaches w wherein the user device comprises a desktop computer, a notebook computer, or a tablet computing device (00040, laptop, desktop, tablets ).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to use personal computing devices as taught by Bui in in the system of Epstein and Bui in order to increase convenience for the end user to user the system.
Consider claim 11, Epstein teaches a system comprising:
data processing hardware (0051, hardware, computer system); and
memory hardware in communication with the data processing hardware and storing instructions that when executed on the data processing hardware causes the data processing hardware to perform operations (0051, software on a computing system, which necessarily must be stored in a memory to be executed) comprising:
during a current stage in a multi-stage voice activity corresponding to a series of user interactions between a user and an application executing on a user device associated with the user (0004, conversational speech systems, figures 2-4, system returns to prompt generation after recognition, indicating multi-turn dialog), receiving a transcription request for a voice input captured by the user device (i.e. figure 2, steps 250, and step 200, figure 3, steps 350, and step 300, steps 450, and step 400, system prompts, user speaks), the transcription request comprising:
audio data indicating the voice input (figure 2, steps 250, figure 3, steps 350, figure 4, steps 450, user speaks); and
dialog history data indicating a prior stage from the multi-stage voice activity (figure 2, steps 210, 220, figure 3, steps 310, 320, figure 4, steps 410, 420, 0044, prompt is provided to prompt analysis module to determine possible responses by the user);
providing, for input to a language model, a set of n-grams associated with the current stage in the multi-stage voice activity (0025, determining a set of n-grams associated with possible responses), the set of n-grams associated with the current stage in the multi-stage voice activity biasing the language model to increase probability scores indicated by the language model of n-grams in the set of n-grams (0041,43, 0047, 0050, boosting n-gram probabilities for words user is likely to say ); and
based on the dialog history data, processing, using the biased language model, the audio data to generate a transcription of the voice input (0041,43, 0047, 0050, boosting n-gram probabilities for words user is likely to say based on dialog prompt, i.e. history, and preforming recognition).
Epstein does not specifically teach dialog history data indicating a prior stage from the multi-stage voice activity that corresponds to a prior transcription request preceding the transcription request; and
wherein the current stage in the multi-stage voice activity is determined based on the prior stage indicated by the dialog history data.
In the same field of dialog systems, Bui teaches dialog history data indicating a prior stage from the multi-stage voice activity that corresponds to a prior transcription request preceding the transcription request (0060-61, dialog state history tracking, also see column 274 in figure 2B-D); and
wherein the current stage in the multi-stage voice activity is determined based on the prior stage indicated by the dialog history data (0057, current dialog state uses dialog history up until that point to determine current dialog state).
It would have been obvious to one of ordinary skill in the art at the time of effective filing to use dialog history to determine dialog state as taught by Bui in the system of Epstein in order to improve the ability for the system to more accurately narrow down possible inputs by the user (Bui 0005).
Claim 12 contains similar limitations as claim 2 and is therefore rejected for the same reasons.
Claim 13 contains similar limitations as claim 3 and is therefore rejected for the same reasons.
Claim 15 contains similar limitations as claim 5 and is therefore rejected for the same reasons.
Claim 16 contains similar limitations as claim 6 and is therefore rejected for the same reasons.
Claim 17 contains similar limitations as claim 7 and is therefore rejected for the same reasons.
Claim 18 contains similar limitations as claim 8 and is therefore rejected for the same reasons.
Claim 19 contains similar limitations as claim 9 and is therefore rejected for the same reasons.
Claim 20 contains similar limitations as claim 10 and is therefore rejected for the same reasons.
Claim(s) 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Epstein and Bui as applied claims 1 and 11 above, and further in view of Stent et al. (US PAP 2015/0149168).
Consider claim 4, Epstein and Bui teach the computer-implemented method of claim 1, but do not specifically teach wherein the operations further comprise, prior to receiving the transcription request for the voice input captured by the user device, receiving a user input indication to activate a mode on the user device that enables the user device to detect voice inputs.
In the same field of dialog systems, Stent teaches wherein the operations further comprise, prior to receiving the transcription request for the voice input captured by the user device, receiving a user input indication to activate a mode on the user device that enables the user device to detect voice inputs (0050, user may use a push-to-talk button or icon to activate recognition).
It would have been obvious to one or ordinary skill in the art at the time of effective filing to use push to talk as taught by Stent in the system of Epstein and Bui in order to use a well-known method of reducing false recognitions or erroneous speech.
Claim 14 contains similar limitations as claim 4 and is therefore rejected for the same reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DOUGLAS C GODBOLD whose telephone number is (571)270-1451. The examiner can normally be reached 6:30am-5pm Monday-Thursday.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Flanders can be reached at (571)272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
DOUGLAS GODBOLD
Examiner
Art Unit 2655
/DOUGLAS GODBOLD/Primary Examiner, Art Unit 2655
