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 .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3, 5, 7, 11-12, 14, 16-17, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Gupta et al, US Patent Pub. 20240411808 A1, in view of Bodigutla, US Patent 12327562 B1, and further in view of Mahajan et al, US Patent Pub. 20220159047 A1. (The Mahajan et al reference is cited in IDS filed 05/02/2025)
Re Claim 1, Gupta et al discloses a method comprising: establishing a user call on a telecommunications network (fig. 1: 115; para 0068: user device 115 can include a phone that initiates calls(bidirectional communication) via telecommunication networks, where the phone will naturally include a phone number), the user call comprising a user phone number (fig. 1: 115; para 0068: user device 115 can include a phone that initiates calls(bidirectional communication) via telecommunication networks, where the phone will naturally include a phone number); establishing a bidirectional communication connection with the user on a telecommunications network (fig. 1: 115; para 0068: user device 115 can include a phone that initiates calls(bidirectional communication) via telecommunication networks, where the phone will naturally include a phone number); receiving audio data from the user and sending the audio data to a speech to text (STT) service (para 0247: text is obtained from speech based voice prompt via a speech-to-text function as highlighted in paras 0039-0040); receiving, from the STT service, text data representing the audio data (para 0247: text is obtained from speech based voice prompt via a speech-to-text function as highlighted in paras 0039-0040); identifying, within the text data, a complete statement of the user (para 0092: spoken words/speech are recognized and converted to texts with the texts being analyzed to understand the user’s intent and extract relevant information; para 0127); sending an AI prompt to an AI model (para 0247: voice prompt is sent to machine-learned large language model (AI) and receiving a digital text message from the machine-learned large language model (AI) then transforming the digital text message to a speech-based voice response via TTS as highlighted in para 0138); receiving a text response from the AI model (para 0247: voice prompt is sent to machine-learned large language model (AI) and receiving a digital text message from the machine-learned large language model (AI) then transforming the digital text message to a speech-based voice response via TTS as highlighted in para 0138); parsing the text response into one or more response statements (para 0127: language parsing for the input uttered speech converted to text; para 0247: machine learned large language model (AI) naturally performs tokenization/parsing for its text outputs similar to the parsing of the converted speech at the input); sending the one or more response statements to a text to speech (TTS) service (para 0247: voice prompt is sent to machine-learned large language model (AI) and receiving a digital text message from the machine-learned large language model (AI) then transforming the digital text message to a speech-based voice response via TTS as highlighted in para 0138); receiving a stream of speech data from the TTS service (para 0247: voice prompt is sent to machine-learned large language model (AI) and receiving a digital text message from the machine-learned large language model (AI) then transforming the digital text message to a speech-based voice response via TTS as highlighted in para 0138); but fails to disclose generating an AI prompt based on the complete statement and converting the speech data to a format suitable for the telecommunications network; determining a target bitrate for the converted speech data; and sending the converted speech data to the user at the target bitrate. However, Bodigutla et al teaches the concept of receiving an audio utterance, converting it to text, analyzing the text to ascertain intent and then subsequently generating an AI prompt (Bodigutla et al, col. 33, lines 44-62: prompt data is generated). It would have been obvious to modify Gupta et al such that it includes an AI prompt generator after the intent of the converted text is determined as taught in Bodigutla et al for the purpose of ensuring that the prompt is ideal to obtain the best answers from the AI model.
Mahajan et al teaches the concept of transcoding audio content into an appropriate format for transmission at a particular/target bitrate to one or more recipient devices (Mahajan et al, para 0049). It would have been obvious to modify the Gupta et al system such that it includes the ability to transcode audio content into an appropriate format for transmission at a particular/target bitrate to another device as taught in Mahajan et al for the purpose of obtaining optimal network performance and high-quality user experience.
Re Claim 3, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, comprising: prior to identifying the complete statement of the user, sending an initialization prompt to the AI model, the initialization prompt providing the AI model with a context of the conversation (Gupta et al, para 0112: prompt message can be modified by adding context information).
Re Claim 5, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, comprising: prior to identifying the complete statement of the user, sending a predetermined opening statement to the user (Bodigutla col. 5, lines 26-43: wakeword).
Re Claim 7, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, wherein generating the AI prompt comprises appending a conversation history associated with the user to the complete statement (Gupta et al, para 0132: history, where the history is constantly updated/appended with the new latest prompt), and wherein generating the AI prompt comprises appending a context prompt to the complete statement (Gupta et al, para 0112: prompt message can be modified by adding context information), wherein the context prompt provides the AI model with instructions defining a desired response (Gupta et al, para 0112: prompt message can be modified by adding context information).
Re Claim 11, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, wherein the prompt (Bodigutla, col. 15, lines 8-13: storing of previous user interactions includes storing of prompts and responses) and the response statement are stored in a repository associated with the user (Bodigutla, col. 15, lines 8-13: storing of previous user interactions includes storing of prompts and responses; col. 28, lines 1-5).
Claim 12 has been analyzed and rejected according to claim 1.
Claim 14 has been analyzed and rejected according to claim 3.
Claim 16 has been analyzed and rejected according to claim 5.
Claim 17 has been analyzed and rejected according to claim 1.
Claim 19 has been analyzed and rejected according to claim 3.
Claims 2, 4, 13, 15, 18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Gupta et al, US Patent Pub. 20240411808 A1, Bodigutla, US Patent 12327562 B1, and Mahajan et al, US Patent Pub. 20220159047 A1, as applied to claim 1 above, in view of Rajakaruna, US Patent Pub. 20230306962 A1. (The Rajakaruna reference is cited in IDS filed 05/02/2025)
Re Claim 2, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, but fail to disclose wherein the bidirectional communication connection is a WebSocket connection. However, Rajakaruna teaches the concept of transmitting audio information via websocket (Rajakaruna, paras 0067, 0069). It would have been obvious to modify the Gupta et al system such it establishes connection via websocket as taught in Rajakaruna for the purpose of minimizing polling delays and HTTP request-response overhead.
Re Claim 4, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 3, wherein the initialization prompt comprises previous conversation history associated with the user (Gupta et al, para 0132: history); but fail to disclose wherein the initialization prompt is based on the user phone number. However, Rajakaruna teaches the concept of including a phone number in the initial prompt (Rajakaruna, para 073). It would have been obvious to modify the Gupta et al system such it includes a phone number within its initial prompt as taught in Rajakaruna for the purpose of being able to track call history.
Claim 13 has been analyzed and rejected according to claim 2.
Claim 15 has been analyzed and rejected according to claim 4.
Claim 18 has been analyzed and rejected according to claim 2.
Claim 20 has been analyzed and rejected according to claim 4.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Gupta et al, US Patent Pub. 20240411808 A1, Bodigutla, US Patent 12327562 B1, and Mahajan et al, US Patent Pub. 20220159047 A1, as applied to claim 1 above, in view of Kneller et al, US Patent Pub. 20210256417 A1. (The Kneller et al reference is cited in IDS filed 05/02/2025)
Re Claim 6, the combined teachings of Gupta et al, Bodigutla and Mahajan et al disclose the method of claim 1, but fail to explicitly disclose wherein the text data representing the audio data includes punctuation, and wherein the punctuation is used to identify the complete statement of the user. However, Kneller et al teaches the concept of natural language processing using sentence breaking techniques such as punctuation marks (Kneller et al, paras 0026-0027). It would have been obvious to modify Gupta et al such that its natural language processing includes sentence breaking techniques such as punctuation marks as taught in Kneller et al for the purpose of being able to appropriately understand contexts thus leading to more optimized responses from AI.
Allowable Subject Matter
Claims 8-10 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter for claims 8-9: The prior art does not teach or moderately suggest the following limitations:
Wherein parsing the text response comprises identifying a function call within the text response; executing the function call; receiving a function return; generating an updated prompt comprising the function return; and sending the updated prompt to the AI model.
Limitations such as these may be useful in combination with other limitations of claim 1.
The following is a statement of reasons for the indication of allowable subject matter for claim 10: The prior art does not teach or moderately suggest the following limitations:
Wherein the format suitable for the telecommunications network is a PCM format generated using a u-law algorithm, and wherein the target bitrate is determined based on a maximum allowable delay minus a communication latency.
Limitations such as these may be useful in combination with other limitations of claim 1.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GEORGE C MONIKANG whose telephone number is (571)270-1190. The examiner can normally be reached Mon. - Fri., 9AM-5PM, ALT. Fridays off.
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/GEORGE C MONIKANG/Primary Examiner, Art Unit 2692 08/13/2026
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