Ian Lane

Deep Recurrent Neural Networks for Acoustic Modelling

2015 · arXiv (Cornell University)

We present a novel deep Recurrent Neural Network (RNN) model for acoustic modelling in Automatic Speech Recognition (ASR). We term our contribution as a TC-DNN-BLSTM-DNN model, the model combines a Deep Neural Network (DNN) with …

Joint Online Spoken Language Understanding and Language Modeling with Recurrent Neural Networks

2016 · arXiv (Cornell University)

Speaker intent detection and semantic slot filling are two critical tasks in spoken language understanding (SLU) for dialogue systems. In this paper, we describe a recurrent neural network (RNN) model that jointly performs intent detection, …

Iterative policy learning in end-to-end trainable task-oriented neural dialog models

2017 · 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

In this paper, we present a deep reinforcement learning (RL) framework for iterative dialog policy optimization in end-to-end task-oriented dialog systems. Popular approaches in learning dialog policy with RL include letting a dialog agent to …

Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

2016

Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition. In this work, we propose an attention-based neural network model for joint intent detection and slot filling, both of …