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AMTA 2020 Conference Videos

by | February 2, 2022
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Demo – Systran
Demo – CustomMT
Demo – Facebook
Demo – Intento
C3 – A Survey of Qualitative Error Analysis for Neural Machine Translation Systems
C10 – Flexible Customization of a Single Neural MT System with Multi dimensional Metadata Inputs
C10 – Flexible Customization of a Single Neural MT System with Multi dimensional Metadata Inputs
Welcome and Keynote – MT Developments in the European Union
K2 – Faithfulness in natural language generation in an era of heightened ethical AI awareness
K3 – Welcome and Keynote – Factor 1000 Better MT, more content, and what we can do with it
K4 – Keynote – Navigating Change Keys to implementing language technology in government
K5 – Using language technology to enable two way communication in humanitarian assistance
K6 – Keynote – Research stories from Google Translate’s Transcribe Mode
G1 – Successful Tech Transfer of MT Research in Government
G2 – Plugging into Trados Augmenting Translation in the Enclave

G3 – PEMT for the Public Sector Discovery, Scoping, and Delivery
G4 – Shareable TTS Components
G5 – A Tale of Eight Countries or the EU Council Presidency Translator in Retrospect
G6 – American Sign Language ASL to English Machine Translation
G7 – Why is it so Hard to Develop Comparable Translation Evaluations and How Can Standards Help
G8 – Using Contemporary US Government Data to Train Custom MT for COVID 19
R3 – Machine Translation with Unsupervised Length Constraints
R4 – Constraining the Transformer NMT Model with Heuristic Grid Beam Search
R6 – Generative latent neural models for automatic word alignment
R7 – The Impact of Indirect Machine Translation on Sentiment Classification
R8 – Towards Handling Compositionality in Low Resource Bilingual Word Induction
R9 – The OpenNMT Neural Machine Translation Toolkit 2020 Edition
R10 – The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020
R11 – THUMT An Open Source Toolkit for Neural Machine Translation
R12 – Panel on Open Source NMT Toolkit Development
R13 – Dynamic Masking for Improved Stability in Online Spoken Language Translation
R14 – On Target Segmentation for Direct Speech Translation
R15 – Domain Robustness in Neural Machine Translation
R16 – Low Resource NMT: A Study on the Effect of Rich Morphological Word Segmentation on Inuktitut
C1 – Operationalizing MT quality estimation
R2 – Investigation of Transformer based Latent Attention Models for Neural Machine Translation
C4 – COMET Deploying a New State of the art MT Evaluation Metric in Production
C5 – Scaling up automatic translation for software: reduction of PEMT volume with customer impact
C6 – Auto MT Quality Prediction Solution and Best Practice
A language comparison of human evaluation & quality estimation
C8 – Machine translation quality across demographic dialectal variation in Social Media
C9 – Making the business case for adopting MT
C11 – Enhance CX with Neural Machine Translation Technolog
C13 – Use MT to Simplify and Speed Up Your Alignment for TM Creation
C14 – Selection of MT Systems in Translation Workflows
C15 – Beyond MT Opening Doors for an NLP Pipeline
C16 – Building Multi Purpose MT Portfolio
C17 – Simultaneous Speech Translation in Google Translate
C18 – Understanding Challenges to Enterprise Machine Translation Adoption
C19 – Lexically Constrained Decoding for Sequence Generation
C20 – Building Salesforce Neural Machine Translation System
C21 – Interactive Adaptation of Neural MT on Commercial Datasets
C22 – Enabling New MT Post Editing Scenarios with Continuous Localization
AMTA Business Meeting
NMT Domain Adaptation Techniques
W2 – iMpacT 2020 (Part 2)
W2 – Virtual Workshop on the Impact of Machine Translation iMpacT 2020
Demo – Amazon
Demo – XTM
R5 – Machine Translation System Selection from Bandit Feedback
W1 – 1st Workshop on Post Editing in Modern Day Translation PEMDT1
T1 – Quick Start Guide to Understanding & Working with Machine Translation