3rd Annual
Artificial Intelligence, Machine Translation
and Language Processing Symposium 2020
24-25 June 20202 Days, 16 Speakers
Virtual Conference - All Online
100% Free
This conference has ended. Replays available.
Detailed Presentations By Session Day | ||||
This conference has ended. Replays available.
Detailed Presentations By Session Day | ||


REPLAYS
Video replays and presentation slide downloads are now available.
Day 2 – Thursday 25 June 2020 – Full Agenda
19:00 AEDT 15:00 ICT 08:00 GMT 10:00 CEST 04:00 EST 01:00 PDT | Bob Hayward ![]() |
KEYNOTE
The AI-Fueled Organisation
AI-fueled organisations demonstrate a sustained commitment to redesigning core systems, processes, and business strategies around AI and its possibilities. They are shifting from a mindset of, “Why should I include AI?” to, “Why would I not?”.
This presentation explains how AI’s role in the enterprise is growing with cognitive, machine learning, automation, and natural language processing being embedded into systems, processes, services, and product offerings.
Keywords: Artificial Intelligence, AI Questions, NLP, Natural Language Processing, Machine Learning, Processesses.
20:00 AEDT 16:00 ICT 09:00 GMT 11:00 CEST 05:00 EST 02:00 PDT | Dion Wiggins Philipp Koehn Professor of Computer Science ![]() ![]() |
Secrets to Customizing a High Quality Neural Machine Translation Engine
With the advent of Neural Machine Translation (NMT), the task and process of customizing a high-quality machine translation system have changed and become more complex. While generic machine translation has become somewhat of a commodity service, high-quality custom engines that truly deliver results are elusive for most. Omniscien Technologies provides generic industry domain engines that are suitable for many general-purpose tasks, but our specialty is customized machine translation engines that are built for a specialized purpose.
This webinar takes a step by step approach to explaining what is involved in the creation of a high-quality neural machine translation engine of your own. We will provide real-world examples and demonstrate the clear benefits of a customized MT system over a generic MT engine.
Join Professor Philipp Koehn, one of the key pioneers in machine translation research and Dion Wiggins, Omniscien Technologies Chief Technology Officer for a key session of insights and information.
Keywords: Machine Translation, Trends and Directions, Productivity, Innovation, Artificial Intelligence, Machine Learning, Deep Learning, Industry Experts, Expert Panels, Expert Presentations, Natural Language Processing, NLP, AI, MT, Onsite Translation, Secure Translation, Private Translation, Enterprise Translation.
21:00 AEDT 17:00 ICT 10:00 GMT 12:00 CEST 06:00 EST 03:00 PDT | Renato Beninatto ![]() |
The Role of Machine Translation in Customer Support Scenarios
Customer Support and User Generated Content are the poor cousins of content. There is never budget left to properly translate and localize it. Community forums for users to share experiences and solve problems collectively and multilingual chatbots are possible solutions, but do they work? Let’s talk about how scalable existing solutions are for customer support environments.
Keywords: Language Service Provider, Language Industry Trends, Patterns in the Language Services Industry, Customer Support.
23:00 AEDT 19:00 ICT 12:00 GMT 14:00 CEST 08:00 EST 05:00 PDT | Serge Gladkoff ![]() |
The New Frontier: Shaping Up Symbiosis of Human and Artificial Intelligence
The language industry is truly already very far into the unchartered territory without proper tools and knowledge. The humanity is playing with a new toy which is far more complex than design of a nuclear power plant and physics of nuclear fission. Yet we are building and running and using the machines and at the same time fear that human professionals will be out of their jobs, falling into the hype of “human parity” and cannot properly measure quality. But all the exciting things that yet are to happen will be discovered on this frontier.
The industry desperately needs explorers of the last mile – the gap between professional human work and “good” MT output, and this is what this presentation is about.
Keywords:Language Service Provider, Artificial Intelligence, Machine Translation.
01:00 AEDT+1 21:00 ICT 14:00 GMT 16:00 CEST 10:00 EST 07:00 PDT | ParaCrawl and EuroPat Consortium Members
|
Amir Kamran – TAUS
Dion Wiggins – Omniscien Technologies
Gema Ramírez-Sánchez – Prompsit
Miquel Esplà – Universitat d’Alacant
Philipp Koehn – Omniscien Technologies /
Philipp Koehn – Johns Hopkins University
Kenneth Heafield – University of Edinburgh
EXPERT PANEL
Big Data, Small World – Tools, Tech and Data: Creating Billions of Bilingual Sentences
ParaCrawl and EuroPat are two large-scale efforts to collect translation data for many languages from the web and other high-volume data sources. The projects are funded by the European Union through the Connected Europe Facility to create the largest known parallel corpora for the official languages of the European Union, and other European languages of interest.
The ParaCrawl project has already made parallel corpora with billions of words per language pair available. ParaCrawl also develops novel methods for document alignment, sentence alignment, and corpus cleaning and releases its processing pipeline as open source tools.
The EuroPat project is working to prepare, align and match patent documents across many languages and domains. While leveraging the base set of technologies developed as part of ParaCrawl, EuroPat further extents technical content coverage with millions of high-quality human translated patent documents and new patent specific tools and processes.
An overview of the ParaCrawl and EuroPat projects, their history, technologies, processes, and resulting data will be presented followed by a panel discussion with several of the ParaCrawl and EuroPat consortium members.
Keywords: Data Mining, Data Manufacturing, Data Synthesis, Crawling, ParaCrawl, Alignment, Parallel Corpus, Patent, EuroPat, Workflow, Pipeline, Parallel Corpora.