1.6k citations · 4.2k across the 75 of their papers we have counts for
8 papers · 1 filter
Towards better decoding and language model integration in sequence to sequence models
Jan Chorowski, Navdeep Jaitly
The recently proposed Sequence-to-Sequence (seq2seq) framework advocates replacing complex data processing pipelines, such as an entire automatic speech recognition system, with a…
Protein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning
Akosua Busia, Jasmine Collins, Navdeep Jaitly
Recently developed deep learning techniques have significantly improved the accuracy of various speech and image recognition systems. In this paper we adapt some of these technique…
RNN Approaches to Text Normalization: A Challenge
Richard Sproat, Navdeep Jaitly
This paper presents a challenge to the community: given a large corpus of written text aligned to its normalized spoken form, train an RNN to learn the correct normalization functi…
Very Deep Convolutional Networks for End-to-End Speech Recognition
Yu Zhang, William Chan, Navdeep Jaitly
Sequence-to-sequence models have shown success in end-to-end speech recognition. However these models have only used shallow acoustic encoder networks. In our work, we successively…
Latent Sequence Decompositions
William Chan, Yu Zhang, Quoc Le +1
We present the Latent Sequence Decompositions (LSD) framework. LSD decomposes sequences with variable lengthed output units as a function of both the input sequence and the output…
Reward Augmented Maximum Likelihood for Neural Structured Prediction
Mohammad Norouzi, Samy Bengio, Zhifeng Chen +4
A key problem in structured output prediction is direct optimization of the task reward function that matters for test evaluation. This paper presents a simple and computationally…
Learning Online Alignments with Continuous Rewards Policy Gradient
Yuping Luo, Chung-Cheng Chiu, Navdeep Jaitly +1
Sequence-to-sequence models with soft attention had significant success in machine translation, speech recognition, and question answering. Though capable and easy to use, they req…
Chained Predictions Using Convolutional Neural Networks
Georgia Gkioxari, Alexander Toshev, Navdeep Jaitly
In this paper, we present an adaptation of the sequence-to-sequence model for structured output prediction in vision tasks. In this model the output variables for a given input are…