Federated Learning for Emoji Prediction in a Mobile Keyboard
Abstract
We show that a word-level recurrent neural network can predict emoji from text typed on a mobile keyboard. We demonstrate the usefulness of transfer learning for predicting emoji by pretraining the model using a language modeling task. We also propose mechanisms to trigger emoji and tune the diversity of candidates. The model is trained using a distributed on-device learning framework called federated learning. The federated model is shown to achieve better performance than a server-trained model. This work demonstrates the feasibility of using federated learning to train production-quality models for natural language understanding tasks while keeping users' data on their devices.
- Publication:
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arXiv e-prints
- Pub Date:
- June 2019
- DOI:
- 10.48550/arXiv.1906.04329
- arXiv:
- arXiv:1906.04329
- Bibcode:
- 2019arXiv190604329R
- Keywords:
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- Computer Science - Computation and Language;
- Computer Science - Machine Learning