Machine learning systems for optimizing audio advertisements
US12417470B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 9, 2022 |
| Grant date | Sep 16, 2025 |
| Priority date | — |
| Expiry date | Jan 25, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N21/4394
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of an audio advertising optimization system are disclosed to enable optimization of audio ad play selection and audio ad content creation using machine learning techniques. In embodiments, the system uses audio processing model(s) to extract metadata about audio ads that it receives from advertisers, such as speaker voice characteristics, music characteristics, and types of call-to-action (CTA) used. As the ads are played to users by ad servers, conversion results associated with the ad plays are recorded. Machine learning model(s) are built based on the ad metadata, user metadata, listening context data, and the user conversion results to learn conversion patterns of the ads. The conversion patterns may be used to optimize the play selection of ad servers to improve conversion rates. In embodiments, the conversion patterns may be made available to ad production systems, which may use the data to optimize audio ad content.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.