Multitask Learning for Spoken Language Understanding

58 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Efficient Large-Scale Domain Classification with Personalized Attention (2018, methodology): “Multi-Task learning was used in the context of SLU by Tur (2006) and has been further explored using neural networks for phoneme recognition (Seltzer and Droppo, 2013) and semantic parsing (Fan et al., 2017; Bapna et al., 2017).”
Multitask Learning of Deep Neural Networks for Low-Resource Speech Recognition (2015, background): “Digital Object Identifier 10.1109/TASLP.2015.2422573 semi-automatic approach to preparing a pronunciation dictionary is to first create a small primary dictionary manually, and then extend it to a large dictionary by applying grapheme-tophoneme conversion [1].”
Multi-domain spoken language understanding with transfer learning (2009, background): “To our knowledge, only Tur (2006) has studied transfer learning for the SLU problem.”
Adversarial Adaptation of Synthetic or Stale Data (2017, background): “Spoken language understanding (SLU) is an important component of these examples that allows natural communication between the user and the agent (Tur, 2006; El-Kahky et al., 2014).”
Active learning for semi-supervised multi-task learning (2009, background): “Semi-supervised learning [1, 2, 3, 4] and multi-task learning (MTL) [5, 6, 7, 8] have been investigated separately by many researchers.”