Sequence models for audio scene recognition
US10930301B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 19, 2020 |
| Grant date | Feb 23, 2021 |
| Priority date | — |
| Expiry date | Aug 19, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L25/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method is provided. Intermediate audio features are generated from an input acoustic sequence. Using a nearest neighbor search, segments of the input acoustic sequence are classified based on the intermediate audio features to generate a final intermediate feature as a classification for the input acoustic sequence. Each segment corresponds to a respective different acoustic window. The generating step includes learning the intermediate audio features from Multi-Frequency Cepstral Component (MFCC) features extracted from the input acoustic sequence. The generating step includes dividing the same scene into the different acoustic windows having varying MFCC features. The generating step includes feeding the MFCC features of each of the different acoustic windows into respective LSTM units such that a hidden state of each respective LSTM unit is passed through an attention layer to identify feature correlations between hidden states at different time steps corresponding to different ones of the different acoustic windows.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.