Search Results for author:
Found 11 papers, 2 papers with code
DISGO: Automatic End-to-End Evaluation for Scene Text OCR
This paper discusses the challenges of optical character recognition (OCR) on natural scenes, which is harder than OCR on documents due to the wild content and various image backgrounds.
Incremental Learning from Scratch for Task-Oriented Dialogue Systems
Clarifying user needs is essential for existing task-oriented dialogue systems.
Knowledge Distillation For Recurrent Neural Network Language Modeling With Trust Regularization
Using knowledge distillation with trust regularization, we reduce the parameter size to a third of that of the previously published best model while maintaining the state-of-the-art perplexity result on Penn Treebank data.
End-To-End Speech Recognition Using A High Rank LSTM-CTC Based Model
In this paper, we propose to use a high rank projection layer to replace the projection matrix.
A Teacher-Student Framework for Maintainable Dialog Manager
Specifically, the {``}student{''} is an extended dialog manager based on a new ontology, and the {``}teacher{''} is existing resources used for guiding the learning process of the {``}student{''}.
Source-Critical Reinforcement Learning for Transferring Spoken Language Understanding to a New Language
This paper focuses on the language transferring task given a tiny in-domain parallel SLU corpus.
Cultural Vocal Bursts Intensity Prediction
domain classification
+6
Source Critical Reinforcement Learning for Transferring Spoken Language Understanding to a New Language
An SLU corpus is a monolingual corpus with domain/intent/slot labels.
Cultural Vocal Bursts Intensity Prediction
domain classification
+8
Domain Adversarial Training for Accented Speech Recognition
In this paper, we propose a domain adversarial training (DAT) algorithm to alleviate the accented speech recognition problem.
Training Augmentation with Adversarial Examples for Robust Speech Recognition
This paper explores the use of adversarial examples in training speech recognition systems to increase robustness of deep neural network acoustic models.
