Interactive Visualization and Manipulation of Attention-based Neural Machine Translation

2017-09-01 · EMNLP 2017 9 · Jaesong Lee, Joong-Hwi Shin, Jun-Seok Kim

While neural machine translation (NMT) provides high-quality translation, it is still hard to interpret and analyze its behavior. We present an interactive interface for visualizing and intervening behavior of NMT, specifically concentrating on the behavior of beam search mechanism and attention component. The tool (1) visualizes search tree and attention and (2) provides interface to adjust search tree and attention weight (manually or automatically) at real-time. We show the tool gives various methods to understand NMT.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Machine TranslationNMTTranslation

IVISIT: An Interactive Visual Simulation Tool for system simulation, visualization, optimization, and parameter management

2024-07-22 · Andreas Knoblauch

IVISIT is a generic interactive visual simulation tool that is based on Python/Numpy and can be used for system simulation, parameter optimization, parameter management, and visualization of system dynamics as required, …

Management

Interactive Attention for Neural Machine Translation

2016-10-17 · COLING 2016 12 · Fandong Meng, Zhengdong Lu, Hang Li, Qun Liu

Conventional attention-based Neural Machine Translation (NMT) conducts dynamic alignment in generating the target sentence. By repeatedly reading the representation of source sentence, which keeps fixed after generated b…

Decoder Machine Translation NMT Sentence+1

Active Learning for Interactive Neural Machine Translation of Data Streams

2018-07-30 · CONLL 2018 10 · Álvaro Peris, Francisco Casacuberta

We study the application of active learning techniques to the translation of unbounded data streams via interactive neural machine translation. The main idea is to select, from an unbounded stream of source sentences, th…

Active Learning Machine Translation Translation

Learning an Interactive Attention Policy for Neural Machine Translation

2017-09-01 · MTSummit 2017 9 · Samee Ibraheem, Nicholas Altieri, John DeNero

Machine Translation Translation

Direct-Manipulation Visualization of Deep Networks

2017-08-12 · Daniel Smilkov, Shan Carter, D. Sculley, Fernanda B. Viégas 외

The recent successes of deep learning have led to a wave of interest from non-experts. Gaining an understanding of this technology, however, is difficult. While the theory is important, it is also helpful for novices to …