Enforcing Encoder-Decoder Modularity in Sequence-to-Sequence Models

11/09/2019
by   Siddharth Dalmia, et al.
0

Inspired by modular software design principles of independence, interchangeability, and clarity of interface, we introduce a method for enforcing encoder-decoder modularity in seq2seq models without sacrificing the overall model quality or its full differentiability. We discretize the encoder output units into a predefined interpretable vocabulary space using the Connectionist Temporal Classification (CTC) loss. Our modular systems achieve near SOTA performance on the 300h Switchboard benchmark, with WER of 8.3 17.6 modules which are independent and interchangeable.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/28/2021

Understanding How Encoder-Decoder Architectures Attend

Encoder-decoder networks with attention have proven to be a powerful way...
research
10/04/2022

Enhancing Spatiotemporal Prediction Model using Modular Design and Beyond

Predictive learning uses a known state to generate a future state over a...
research
07/25/2022

Effective and Interpretable Information Aggregation with Capacity Networks

How to aggregate information from multiple instances is a key question m...
research
12/31/2016

Cutting-off Redundant Repeating Generations for Neural Abstractive Summarization

This paper tackles the reduction of redundant repeating generation that ...
research
06/07/2022

LegoNN: Building Modular Encoder-Decoder Models

State-of-the-art encoder-decoder models (e.g. for machine translation (M...
research
10/11/2018

Piano Genie

We present Piano Genie, an intelligent controller which allows non-music...
research
07/04/2016

Towards Abstraction from Extraction: Multiple Timescale Gated Recurrent Unit for Summarization

In this work, we introduce temporal hierarchies to the sequence to seque...

Please sign up or login with your details

Forgot password? Click here to reset