Technology area: Communications
11 pending office actions • 6 art units • 10 examiners • 0 of 11 (0%) have an AI response strategy ready • 13 patents granted in the last 365 days
Soundhound AI Ip LLC currently manages a portfolio of 11 pending office actions within the Communications technology area. These matters are distributed across 10 distinct examiners and 6 distinct art units. The busiest examiner, VU B HANG, is responsible for 2 pending office actions. This distribution suggests that no individual examiner dominates the current prosecution landscape for the company, requiring a strategy that accounts for 10 different perspectives.
The presence of 6 distinct art units reflects a diverse range of technical subject matter within the Communications sector. With 11 pending actions and the examiners involved, the company faces a decentralized prosecution environment. Practitioners should be prepared to navigate the specific standards of 6 different art units while coordinating with the assigned examiners. This variety suggests that the portfolio covers multiple technical sub-categories that are being evaluated independently by the patent office.
Based on the USPTO statutory response window for each pending office action. 2 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 1 (9%) |
| §101 + other | 1 (9%) |
| §103 only | 3 (27%) |
| §102 only | 1 (9%) |
| Double-patenting only | 1 (9%) |
| Multi-statute (no §101) | 4 (36%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| HANG, VU B | 2 | 74.7% | +17.1% |
| ALBERTALLI, BRIAN LOUIS | 1 | 81.8% | +16.8% |
| ABEBE, DANIEL DEMELASH | 1 | 89.7% | +7.4% |
| PULLIAS, JESSE SCOTT | 1 | 82.6% | +12.4% |
| SERROU, ABDELALI | 1 | 74.4% | +29.6% |
| AGAHI, DARIOUSH | 1 | 84.0% | +30.3% |
| SARPONG, AKWASI | 1 | 68.2% | +28.4% |
| SERRAGUARD, SEAN ERIN | 1 | 69.3% | +34.3% |
| SITTNER, MICHAEL J | 1 | 10.8% | +14.8% |
| ARMSTRONG, ANGELA A | 1 | 74.1% | +8.9% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19026132 | BUILDING A NATURAL LANGUAGE UNDERSTANDING APPLICATION USING A RECEIVED ELECTRONIC RECORD CONTAINING PROGRAMMING CODE INCLUDING AN INTERPRET-BLOCK AND AN INTERPRET-STATEMENT | ABEBE, DANIEL DEMELASH | — |
| 19014095 | PERFORMING SPEECH RECOGNITION USING A SET OF WORDS WITH DESCRIPTIONS IN TERMS OF COMPONENTS SMALLER THAN THE WORDS | PULLIAS, JESSE SCOTT | — |
| 18771489 | SERVER SUPPORTED RECOGNITION OF WAKE PHRASES | AGAHI, DARIOUSH | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17580289 | Text-to-Speech Adapted by Machine Learning | ARMSTRONG, ANGELA A | 72d overdue |
| 18783423 | AUTOMATIC LEARNING OF ENTITIES, WORDS, PRONUNCIATIONS, AND PARTS OF SPEECH | SERROU, ABDELALI | 16d |
| 19032434 | TOKEN CONFIDENCE SCORES FOR AUTOMATIC SPEECH RECOGNITION | ALBERTALLI, BRIAN LOUIS | — |
| 18945442 | DERIVING ACOUSTIC FEATURES AND LINGUISTIC FEATURES FROM RECEIVED SPEECH AUDIO | HANG, VU B | — |
| 18461212 | NEURAL SPEECH-TO-MEANING | SERRAGUARD, SEAN ERIN | — |
| 18356659 | ARTIFICIAL INTELLIGENCE SMART ANSWERING ARCHITECTURE | SITTNER, MICHAEL J | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18783423 | AUTOMATIC LEARNING OF ENTITIES, WORDS, PRONUNCIATIONS, AND PARTS OF SPEECH | SERROU, ABDELALI | 16d |
| 19032434 | TOKEN CONFIDENCE SCORES FOR AUTOMATIC SPEECH RECOGNITION | ALBERTALLI, BRIAN LOUIS | — |
| 19014095 | PERFORMING SPEECH RECOGNITION USING A SET OF WORDS WITH DESCRIPTIONS IN TERMS OF COMPONENTS SMALLER THAN THE WORDS | PULLIAS, JESSE SCOTT | — |
| 18945442 | DERIVING ACOUSTIC FEATURES AND LINGUISTIC FEATURES FROM RECEIVED SPEECH AUDIO | HANG, VU B | — |
| 18928627 | METHOD AND SYSTEM FOR ACOUSTIC MODEL CONDITIONING ON NON-PHONEME INFORMATION FEATURES | HANG, VU B | — |
| 18771489 | SERVER SUPPORTED RECOGNITION OF WAKE PHRASES | AGAHI, DARIOUSH | — |
| 18743562 | METHOD AND SYSTEM FOR CONVERSATION TRANSCRIPTION WITH METADATA | SARPONG, AKWASI | — |
| 18461212 | NEURAL SPEECH-TO-MEANING | SERRAGUARD, SEAN ERIN | — |
| Art Unit | Apps |
|---|---|
| 2654 | 2 |
| 2659 | 2 |
| 2656 | 1 |
| 2681 | 1 |
| 2657 | 1 |
| 3621 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19032434 | TOKEN CONFIDENCE SCORES FOR AUTOMATIC SPEECH RECOGNITION | ALBERTALLI, BRIAN LOUIS | — | §102§103§112 | Non-Final OA | — | Pending | Jan 20, 2025 |
| 19026132 | BUILDING A NATURAL LANGUAGE UNDERSTANDING APPLICATION USING A RECEIVED ELECTRONIC RECORD CONTAINING PROGRAMMING CODE INCLUDING AN INTERPRET-BLOCK AND AN INTERPRET-STATEMENT | ABEBE, DANIEL DEMELASH | — | §102Other | Non-Final OA | — | Pending | Jan 16, 2025 |
| 19014095 | PERFORMING SPEECH RECOGNITION USING A SET OF WORDS WITH DESCRIPTIONS IN TERMS OF COMPONENTS SMALLER THAN THE WORDS | PULLIAS, JESSE SCOTT | — | §103 | Non-Final OA | — | Pending | Jan 08, 2025 |
| 18945442 | DERIVING ACOUSTIC FEATURES AND LINGUISTIC FEATURES FROM RECEIVED SPEECH AUDIO | HANG, VU B | 2654 | §102§103 | Non-Final OA | — | Pending | Nov 12, 2024 |
| 18928627 | METHOD AND SYSTEM FOR ACOUSTIC MODEL CONDITIONING ON NON-PHONEME INFORMATION FEATURES | HANG, VU B | 2654 | DP | Non-Final OA | — | Pending | Oct 28, 2024 |
| 18783423 | AUTOMATIC LEARNING OF ENTITIES, WORDS, PRONUNCIATIONS, AND PARTS OF SPEECH | SERROU, ABDELALI | 2659 | §101Other | Final Rejection | 16d | Pending | Jul 25, 2024 |
| 18771489 | SERVER SUPPORTED RECOGNITION OF WAKE PHRASES | AGAHI, DARIOUSH | 2656 | §103 | Final Rejection | — | Pending | Jul 12, 2024 |
| 18743562 | METHOD AND SYSTEM FOR CONVERSATION TRANSCRIPTION WITH METADATA | SARPONG, AKWASI | 2681 | §103 | Final Rejection | — | Pending | Jun 14, 2024 |
| 18461212 | NEURAL SPEECH-TO-MEANING | SERRAGUARD, SEAN ERIN | 2657 | §103§112 | Final Rejection | — | Pending | Sep 05, 2023 |
| 18356659 | ARTIFICIAL INTELLIGENCE SMART ANSWERING ARCHITECTURE | SITTNER, MICHAEL J | 3621 | §101§103§112 | Final Rejection | — | Pending | Jul 21, 2023 |
| 17580289 | Text-to-Speech Adapted by Machine Learning | ARMSTRONG, ANGELA A | 2659 | §103§112 | Final Rejection | 72d overdue | Pending | Jan 20, 2022 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free TrialSoundhound AI Ip LLC has 11 pending office actions as of October 2026, spread across 6 art units and 10 examiners.
Vu B Hang has the most, with 2 of Soundhound AI Ip LLC's pending office actions.
Mostly Communications (USPTO Tech Center 2600), based on where its pending office actions are examined.
