Systems and methods for automatic unit selection and target decomposition for sequence labelling
US10373610B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 7, 2017 |
| Grant date | Aug 6, 2019 |
| Priority date | — |
| Expiry date | Oct 6, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/0636
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are systems and methods for automatic unit selection and target decomposition for sequence labelling. Embodiments include a new loss function called Gram-Connectionist Temporal Classification (CTC) loss that extend the popular CTC loss function criterion to alleviate prior limitations. While preserving the advantages of CTC, Gram-CTC automatically learns the best set of basic units (grams), as well as the most suitable decomposition of target sequences. Unlike CTC, embodiments of Gram-CTC allow a model to output variable number of characters at each time step, which enables the model to capture longer term dependency and improves the computational efficiency. It is also demonstrated that embodiments of Gram-CTC improve CTC in terms of both performance and efficiency on the large vocabulary speech recognition task at multiple scales of data, and that systems that employ an embodiment of Gram-CTC can outperform the state-of-the-art on a standard speech benchmark.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.