Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18885396 | INTERFACE ACCESS PROCESSING METHOD, COMPUTER DEVICE AND STORAGE MEDIUM | September 2024 | November 2025 | Allow | 14 | 3 | 0 | No | No |
| 18749496 | Modular Large Language Model (LLM) Guided Tree-of-Thought System | June 2024 | September 2025 | Allow | 15 | 3 | 0 | Yes | No |
| 18444050 | INTENTION RECOGNITION METHOD AND APPARATUS, READABLE MEDIUM, AND ELECTRONIC DEVICE | February 2024 | September 2025 | Allow | 19 | 3 | 0 | No | No |
| 18517658 | METHODS AND SYSTEMS FOR PROVIDING SUBTITLES | November 2023 | October 2024 | Allow | 11 | 1 | 0 | No | No |
| 18377455 | FRONTEND AUDIO CAPTURE FOR VIDEO CONFERENCING APPLICATIONS | October 2023 | July 2025 | Allow | 22 | 3 | 0 | Yes | No |
| 18449970 | ESTIMATING OUTPUT CONFIDENCE FOR BLACK-BOX API | August 2023 | November 2024 | Allow | 15 | 1 | 0 | No | No |
| 17970943 | Performing Property Estimation Using Quantum Gradient Operation on Quantum Computing System | October 2022 | January 2026 | Allow | 38 | 1 | 0 | Yes | No |
| 17804727 | METHOD AND SYSTEM FOR PREPARING KNOWLEDGEBASE OF MICROBES AND MICROBIAL FUNCTIONS HELPING REDUCING CANCER RISK | May 2022 | September 2025 | Allow | 40 | 1 | 0 | No | No |
| 17732871 | QUANTUM COMPUTER ARCHITECTURE BASED ON MULTI-QUBIT GATES | April 2022 | February 2026 | Allow | 45 | 2 | 0 | No | No |
| 17730963 | OPTIMIZING QUBIT OPERATING FREQUENCIES | April 2022 | August 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17720536 | ARTIFICIAL INTELLIGENCE BASED SYSTEM AND METHOD FOR AUTOMATICALLY MONITORING THE HEALTH OF ONE OR MORE USERS | April 2022 | February 2026 | Abandon | 46 | 1 | 0 | No | No |
| 17669946 | PERFORMING STATE REVERSAL ON A QUANTUM SPIN CHAIN | February 2022 | August 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17631613 | ENCODING AND DECODING IVAS BITSTREAMS | January 2022 | October 2024 | Allow | 33 | 2 | 1 | Yes | No |
| 17630855 | IMPRESSION ESTIMATION APPARATUS, LEARNING APPARATUS, METHODS AND PROGRAMS FOR THE SAME | January 2022 | January 2025 | Abandon | 36 | 4 | 0 | Yes | No |
| 17576492 | METHOD, SYSTEM, AND NON-TRANSITORY COMPUTER READABLE RECORD MEDIUM FOR SPEAKER DIARIZATION COMBINED WITH SPEAKER IDENTIFICATION | January 2022 | November 2025 | Abandon | 46 | 6 | 0 | Yes | No |
| 17573511 | METHOD AND APPARATUS FOR CONSTRUCTING EVENT LIBRARY, ELECTRONIC DEVICE AND COMPUTER READABLE MEDIUM | January 2022 | February 2025 | Abandon | 37 | 2 | 0 | No | No |
| 17619618 | RESTORING APPARATUS, RESTORING METHOD, AND PROGRAM | December 2021 | November 2025 | Abandon | 47 | 1 | 0 | No | No |
| 17553708 | SOUND ENHANCEMENT METHOD AND RELATED COMMUNICATION APPARATUS | December 2021 | February 2025 | Abandon | 38 | 4 | 0 | No | No |
| 17596566 | METHOD AND SYSTEM FOR CODING METADATA IN AUDIO STREAMS AND FOR FLEXIBLE INTRA-OBJECT AND INTER-OBJECT BITRATE ADAPTATION | December 2021 | April 2025 | Allow | 41 | 4 | 0 | No | No |
| 17596567 | METHOD AND SYSTEM FOR CODING METADATA IN AUDIO STREAMS AND FOR EFFICIENT BITRATE ALLOCATION TO AUDIO STREAMS CODING | December 2021 | July 2024 | Allow | 31 | 2 | 0 | No | No |
| 17545815 | CREATIVE WORK SYSTEMS AND METHODS THEREOF | December 2021 | July 2024 | Allow | 31 | 2 | 0 | Yes | No |
| 17545529 | SYSTEMS AND METHODS FOR DETECTING MANUFACTURING ANOMALIES | December 2021 | March 2025 | Allow | 39 | 1 | 0 | Yes | No |
| 17541307 | CONVERSATIONAL AGENT COUNTERFACTUAL SIMULATION | December 2021 | November 2024 | Allow | 35 | 2 | 0 | Yes | No |
| 17456138 | METHOD AND APPARATUS FOR CLASSIFYING ITEM BASED ON MACHINE LEARNING | November 2021 | October 2025 | Abandon | 47 | 1 | 0 | No | No |
| 17524288 | COMPUTING SYSTEM FOR DOMAIN EXPRESSIVE TEXT TO SPEECH | November 2021 | January 2025 | Allow | 38 | 3 | 0 | Yes | No |
| 17521139 | DIVIDE-AND-CONQUER FOR LANE-AWARE DIVERSE TRAJECTORY PREDICTION | November 2021 | February 2025 | Allow | 39 | 1 | 0 | Yes | No |
| 17605139 | NETWORK CONFIGURATION OPTIMIZATION USING A REINFORCEMENT LEARNING AGENT | October 2021 | May 2025 | Abandon | 43 | 1 | 0 | No | No |
| 17500339 | MULTI-TASK NEURAL NETWORK BY MICRO-STRUCTURED PARAMETER SHARING FOR MULTI-QUALITY LOOP FILTER | October 2021 | April 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17486943 | DIALOG INTERACTION METHOD, GRAPHICAL USER INTERFACE, TERMINAL DEVICE, AND NETWORK DEVICE | September 2021 | January 2025 | Abandon | 39 | 2 | 0 | Yes | No |
| 17487732 | RESPONSIVE CATEGORY PREDICTION FOR USER QUERIES | September 2021 | August 2024 | Allow | 35 | 2 | 0 | No | No |
| 17486252 | ELECTRONIC APPARATUS, SYSTEM COMPRISING ELECTRONIC APPARATUS AND SERVER AND CONTROLLING METHOD THEREOF | September 2021 | April 2024 | Allow | 31 | 1 | 0 | No | No |
| 17486877 | AI-BASED LIVESTOCK MANAGEMENT SYSTEM AND LIVESTOCK MANAGEMENT METHOD THEREOF | September 2021 | November 2025 | Allow | 50 | 3 | 0 | Yes | No |
| 17441829 | DETERMINATION OF THE SIGNIFICANCE OF SPATIAL AUDIO PARAMETERS AND ASSOCIATED ENCODING | September 2021 | February 2024 | Allow | 29 | 2 | 0 | No | No |
| 17475724 | METHOD AND SERVER FOR A TEXT-TO-SPEECH PROCESSING | September 2021 | December 2025 | Allow | 51 | 3 | 0 | No | No |
| 17473992 | USING A NATURAL LANGUAGE INTERFACE TO CORRELATE USER INTENT WITH PREDEFINED DATA ANALYSIS TEMPLATES FOR SELECTED DATA SOURCES | September 2021 | July 2024 | Allow | 34 | 2 | 0 | Yes | No |
| 17438460 | Semi-supervised Hyperspectral Data Quantitative Analysis Method Based on Generative Adversarial Network | September 2021 | April 2025 | Allow | 43 | 2 | 0 | No | No |
| 17437947 | NEURAL NETWORK CIRCUIT | September 2021 | August 2025 | Abandon | 47 | 2 | 0 | Yes | No |
| 17472203 | VOICE BASED SEARCHING AND DIALOG MANAGEMENT SYSTEM | September 2021 | September 2024 | Allow | 36 | 4 | 0 | Yes | No |
| 17468568 | SYSTEMS AND METHODS FOR DETECTING EMOTION FROM AUDIO FILES | September 2021 | February 2024 | Allow | 29 | 3 | 0 | Yes | No |
| 17410413 | DYNAMIC ELECTRONIC AGREEMENTS | August 2021 | August 2024 | Abandon | 35 | 4 | 0 | Yes | Yes |
| 17431760 | GENERATION APPARATUS, LEARNING APPARATUS, GENERATION METHOD AND PROGRAM | August 2021 | July 2025 | Abandon | 47 | 4 | 0 | Yes | No |
| 17395131 | DEFECT PREDICTION METHODS, APPARAUTSES, ELECTRONIC DEVICES AND STORAGE MEDIA | August 2021 | November 2025 | Abandon | 51 | 2 | 0 | Yes | No |
| 17394068 | DECODER AND DECODING METHOD FOR LC3 CONCEALMENT INCLUDING FULL FRAME LOSS CONCEALMENT AND PARTIAL FRAME LOSS CONCEALMENT | August 2021 | March 2024 | Allow | 31 | 1 | 1 | No | No |
| 17387720 | SYSTEM AND METHOD FOR GENERATING ONTOLOGIES AND RETRIEVING INFORMATION USING THE SAME | July 2021 | July 2024 | Allow | 36 | 1 | 0 | Yes | No |
| 17375927 | TECHNIQUES FOR AUDIO FEATURE DETECTION | July 2021 | August 2025 | Allow | 49 | 7 | 0 | Yes | No |
| 17369417 | COMPUTER-IMPLEMENTED DATA PROCESSING METHOD, MICRO-CONTROLLER SYSTEM AND COMPUTER PROGRAM PRODUCT FOR APPLYING POOLING WITH RESPECT TO AN OUTPUT BUFFER IN A NEURAL NETWORK | July 2021 | March 2025 | Allow | 44 | 2 | 0 | Yes | No |
| 17363379 | Batch Processing in a Machine Learning Computer | June 2021 | January 2025 | Allow | 43 | 2 | 0 | No | No |
| 17361994 | METHOD OF EVALUATING ROBUSTNESS OF ARTIFICIAL NEURAL NETWORK WATERMARKING AGAINST MODEL STEALING ATTACKS | June 2021 | March 2025 | Abandon | 45 | 2 | 0 | No | No |
| 17419441 | METHOD AND DEVICE FOR IDENTIFYING MACHINE LEARNING MODELS FOR DETECTING ENTITIES | June 2021 | November 2025 | Abandon | 52 | 3 | 0 | No | No |
| 17360015 | Voice Interaction Method, Device, and System | June 2021 | October 2024 | Abandon | 39 | 2 | 0 | No | No |
| 17414705 | Data Generation Device, Predictor Learning Device, Data Generation Method, and Learning Method | June 2021 | November 2025 | Abandon | 53 | 2 | 0 | No | No |
| 17345671 | Ensuring User Data Security While Personalizing a Social Agent | June 2021 | March 2025 | Allow | 45 | 6 | 0 | Yes | No |
| 17309609 | WIRELESS AUDIO TESTING | June 2021 | July 2025 | Abandon | 49 | 4 | 0 | Yes | No |
| 17344293 | METHOD AND SYSTEM FOR ASSIGNING UNIQUE VOICE FOR ELECTRONIC DEVICE | June 2021 | August 2024 | Allow | 38 | 4 | 0 | Yes | No |
| 17335698 | METHOD FOR OPTIMIZING SELECTION OF SUITABLE NETWORK MODEL, APPARATUS ENABLING SELECTION, ELECTRONIC DEVICE, AND STORAGE MEDIUM | June 2021 | September 2025 | Abandon | 51 | 2 | 0 | No | No |
| 17325886 | SYSTEM AND METHOD FOR VOICE BIOMETRICS AUTHENTICATION | May 2021 | March 2024 | Allow | 34 | 3 | 0 | Yes | No |
| 17294697 | Resilient Neural Network | May 2021 | March 2025 | Allow | 46 | 1 | 0 | No | No |
| 17323847 | GENERATION OF OPTIMIZED SPOKEN LANGUAGE UNDERSTANDING MODEL THROUGH JOINT TRAINING WITH INTEGRATED ACOUSTIC KNOWLEDGE-SPEECH MODULE | May 2021 | October 2024 | Allow | 41 | 3 | 0 | Yes | No |
| 17318704 | INTERACTIVE GRAPHICAL INTERFACES FOR EFFICIENT LOCALIZATION OF NATURAL LANGUAGE GENERATION RESPONSES, RESULTING IN NATURAL AND GRAMMATICAL TARGET LANGUAGE OUTPUT | May 2021 | August 2024 | Allow | 39 | 3 | 0 | Yes | No |
| 17315447 | TEXT MINING BASED ON DOCUMENT STRUCTURE INFORMATION EXTRACTION | May 2021 | February 2025 | Allow | 45 | 5 | 0 | Yes | No |
| 17308550 | LOW LATENCY AUDIO PROCESSING TECHNIQUES | May 2021 | May 2025 | Allow | 48 | 5 | 0 | Yes | No |
| 17289220 | OPTIMIZATION DEVICE, GUIDANCE SYSTEM, OPTIMIZATION METHOD, AND PROGRAM | April 2021 | August 2025 | Abandon | 51 | 2 | 0 | No | No |
| 17289227 | QUANTIZING TRAINED LONG SHORT-TERM MEMORY NEURAL NETWORKS | April 2021 | July 2025 | Allow | 51 | 3 | 0 | Yes | No |
| 17238721 | MACHINE LEARNING SYSTEM FOR ASSESSING HEART VALVES AND SURROUNDING CARDIOVASCULAR TRACTS | April 2021 | June 2025 | Abandon | 49 | 1 | 0 | No | No |
| 17237961 | NON-LEXICALIZED FEATURES FOR LANGUAGE IDENTITY CLASSIFICATION USING SUBWORD TOKENIZATION | April 2021 | March 2024 | Allow | 35 | 2 | 0 | Yes | No |
| 17284797 | Method of searching patent documents | April 2021 | January 2026 | Abandon | 57 | 4 | 0 | No | No |
| 17219030 | CLAUSE EXTRACTION USING MACHINE TRANSLATION AND NATURAL LANGUAGE PROCESSING | March 2021 | June 2024 | Allow | 39 | 5 | 0 | Yes | No |
| 17209174 | ARTIFICIAL INTELLIGENCE-BASED QUESTION-ANSWER NATURAL LANGUAGE PROCESSING TRACES | March 2021 | January 2025 | Abandon | 46 | 3 | 0 | Yes | Yes |
| 17207635 | AUDIO-VISUAL ACTIVITY SAFETY RECOMMENDATION WITH CONTEXT-AWARE RISK PROPORTIONAL PERSONALIZED FEEDBACK | March 2021 | September 2025 | Abandon | 54 | 2 | 0 | Yes | No |
| 17207569 | METHODS AND SYSTEMS FOR GENERATING REAL-TIME RECOMMENDATIONS USING MACHINE LEARNING MODELS | March 2021 | July 2025 | Abandon | 52 | 2 | 0 | Yes | No |
| 17207554 | METHODS AND SYSTEMS FOR DETERMINING RECOMMENDATIONS BASED ON REAL-TIME OPTIMIZATION OF MACHINE LEARNING MODELS | March 2021 | November 2025 | Allow | 56 | 3 | 0 | Yes | No |
| 17197740 | SYSTEM AND METHOD FOR DATA AUGMENTATION OF FEATURE-BASED VOICE DATA | March 2021 | April 2024 | Allow | 37 | 4 | 0 | Yes | No |
| 17192651 | Testing of Computing Processes Using Artificial Intelligence | March 2021 | February 2026 | Abandon | 59 | 3 | 0 | Yes | No |
| 17271177 | STATE TRANSITION PREDICTION DEVICE, AND DEVICE, METHOD, AND PROGRAM FOR LEARNING PREDICTIVE MODEL | February 2021 | September 2025 | Abandon | 55 | 3 | 0 | Yes | No |
| 17271182 | ELECTRONIC APPARATUS FOR PROCESSING USER UTTERANCE AND CONTROLLING METHOD THEREOF | February 2021 | October 2024 | Allow | 44 | 3 | 0 | Yes | No |
| 17161933 | KNOWLEDGE GRAPH EMBEDDING USING GRAPH CONVOLUTIONAL NETWORKS WITH RELATION-AWARE ATTENTION | January 2021 | February 2026 | Abandon | 60 | 4 | 0 | Yes | No |
| 17122778 | METHOD FOR IMPROVING THE USER TRAINING EXPERIENCE ON AN EXERCISE MACHINE AND EXERCISE MACHINE IMPLEMENTING SUCH METHOD | December 2020 | October 2024 | Abandon | 46 | 4 | 0 | No | No |
| 17110022 | Federated machine-Learning platform leveraging engineered features based on statistical tests | December 2020 | October 2024 | Allow | 47 | 1 | 0 | No | No |
| 17094278 | MACHINE LEARNING FOR TRANSLATION TO STRUCTURED COMPUTER READABLE REPRESENTATION | November 2020 | September 2025 | Allow | 58 | 4 | 0 | Yes | Yes |
| 17081640 | Low Complexity Voice Activity Detection Algorithm | October 2020 | June 2024 | Abandon | 44 | 2 | 0 | No | Yes |
| 17002407 | MULTI-TOKEN EMBEDDING AND CLASSIFIER FOR MASKED LANGUAGE MODELS | August 2020 | January 2025 | Abandon | 53 | 5 | 0 | Yes | Yes |
| 16186939 | COGNITIVE ANALYSIS FOR IDENTIFICATION OF SENSORY ISSUES | November 2018 | October 2025 | Abandon | 60 | 4 | 0 | Yes | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner LEE, MICHAEL CHRISTOPHER.
With a 33.3% reversal rate, the PTAB reverses the examiner's rejections in a meaningful percentage of cases. This reversal rate is above the USPTO average, indicating that appeals have better success here than typical.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 20.0% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the bottom 25% across the USPTO, indicating that filing appeals is less effective here than in most other areas.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
⚠ Filing a Notice of Appeal shows limited benefit. Consider other strategies like interviews or amendments before appealing.
Examiner LEE, MICHAEL CHRISTOPHER works in Art Unit 2128 and has examined 66 patent applications in our dataset. With an allowance rate of 57.6%, this examiner allows applications at a lower rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 45 months.
Examiner LEE, MICHAEL CHRISTOPHER's allowance rate of 57.6% places them in the 18% percentile among all USPTO examiners. This examiner is less likely to allow applications than most examiners at the USPTO.
On average, applications examined by LEE, MICHAEL CHRISTOPHER receive 2.74 office actions before reaching final disposition. This places the examiner in the 80% percentile for office actions issued. This examiner issues more office actions than most examiners, which may indicate thorough examination or difficulty in reaching agreement with applicants.
The median time to disposition (half-life) for applications examined by LEE, MICHAEL CHRISTOPHER is 45 months. This places the examiner in the 12% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +21.9% benefit to allowance rate for applications examined by LEE, MICHAEL CHRISTOPHER. This interview benefit is in the 67% percentile among all examiners. Recommendation: Interviews provide an above-average benefit with this examiner and are worth considering.
When applicants file an RCE with this examiner, 25.0% of applications are subsequently allowed. This success rate is in the 38% percentile among all examiners. Strategic Insight: RCEs show below-average effectiveness with this examiner. Carefully evaluate whether an RCE or continuation is the better strategy.
This examiner enters after-final amendments leading to allowance in 20.0% of cases where such amendments are filed. This entry rate is in the 24% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 0.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 5% percentile among all examiners. Note: Pre-appeal conferences show limited success with this examiner compared to others. While still worth considering, be prepared to proceed with a full appeal brief if the PAC does not result in favorable action.
This examiner withdraws rejections or reopens prosecution in 25.0% of appeals filed. This is in the 3% percentile among all examiners. Strategic Insight: This examiner rarely withdraws rejections during the appeal process compared to other examiners. If you file an appeal, be prepared to fully prosecute it to a PTAB decision. Per MPEP § 1207, the examiner will prepare an Examiner's Answer maintaining the rejections.
When applicants file petitions regarding this examiner's actions, 100.0% are granted (fully or in part). This grant rate is in the 90% percentile among all examiners. Strategic Note: Petitions are frequently granted regarding this examiner's actions compared to other examiners. Per MPEP § 1002.02(c), various examiner actions are petitionable to the Technology Center Director, including prematureness of final rejection, refusal to enter amendments, and requirement for information. If you believe an examiner action is improper, consider filing a petition.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 10% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 10% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.