Method for using a multi-scale recurrent neural network with pretraining for spoken language understanding tasks
US9607616B2 · kind B2 · utility
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6Claims
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Key dates
| Filing date | Aug 17, 2015 |
| Grant date | Mar 28, 2017 |
| Priority date | — |
| Expiry date | Sep 13, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/223
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A spoken language understanding (SLU) system receives a sequence of words corresponding to one or more spoken utterances of a user, which is passed through a spoken language understanding module to produce a sequence of intentions. The sequence of words are passed through a first subnetwork of a multi-scale recurrent neural network (MSRNN), and the sequence of intentions are passed through a second subnetwork of the multi-scale recurrent neural network (MSRNN). Then, the outputs of the first subnetwork and the second subnetwork are combined to predict a goal of the user.
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