Identifying shifts in audio content via machine learning
US11935520B1 · kind B1 · utility
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14Claims
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Key dates
| Filing date | Dec 16, 2020 |
| Grant date | Mar 19, 2024 |
| Priority date | — |
| Expiry date | Jun 18, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/081
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system for identifying the beginning and ending of songs via a machine learning analysis. A machine learning model analyzes streaming audio (such as a radio broadcast) in overlapping, 3-second samples. Each sample is labeled into groups such as “song,” “talk,” “commercial” and “transition.” Based on the location of the transition samples, an exact second a given song begins and ends in the audio stream is derivable. The model further identifies when two songs shift between one another.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.