24-25 June 2020
2 Days, 16 Speakers
Virtual Conference - All Online
Video replays and presentation slide downloads are now available.
Found in Translation – Language Meets Technology
Language is highly complex. Technologies to process and understand and create language related data are evolving quickly. In today’s competitive world, organizations that understand their staff and their customers via data analytics have a considerable strategic competitive advantage. At the same time, there is a lot of hype and misinformation. This opening keynote presentation looks at the current state of language technology in the context of artificial intelligence, machine learning, machine translation and language processing, cutting through the hype to look at real world applications of these technologies in business today. The following 2 days are packed with industry experts, with this presentation acting as a primer ahead of more in-depth discussions.
Dion will introduce some key concepts on a range of topics including deep neural machine translation and artificial intelligence to outline how AI tools can be integrated into language processing workflows that break down language and language barriers. Finally, Dion will explore how language processing in both bilingual and monolingual contexts can find new information that is hidden from the human eye but is actually right in front of us to use in everyday business.
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.
Leadership Effectiveness Enabled by Artificial Intelligence
KeenCorp provides business leaders a complete, unbiased, real-time leading indicator of their risk and performance culture. KeenCorp’s software processes digital, written communication to measure tension and personal involvement of employee groups, based on data in existing company workflow. Individual employee privacy (GDPR-compliance), client confidentiality, and security are ensured. The KeenCorp Index analyzes behavioral patterns across the organization on a daily basis and identifies blind spots that go undetected by traditional management control systems. With this business leaders can better manage culture, productivity, and profitability by connecting with employees when and where it matters. This is especially relevant for today’s remote workforce due to COVID-19. KeenCorp’s founder and CEO, Viktor Mirovic will elaborate on its technology and take the Symposium audience through some recent use cases.
Keywords: Natural Language Processing, Sentiment Analysis, Named Entity Recognition, Employee Engagement, Corporate Culture, Data Mining, Artificial Intelligence.
On-Premises Secure Translation and Workflow Automation
Secure, private, on-premises machine translation is now a key priority for many organizations when automating their translation workflows. Private cloud and on-premises solutions are often preferred to hosted cloud solutions to limit the risk of transmitting personal data and to have additional levels of control that are desirable to meet GRPR and other compliance requirements.
This presentation will walk through several scenarios where Omniscien’s Language Studio Enterprise Translation Server (LSETS) has been deployed in real-world applications and look at how workflow technologies have played a major role beyond just the machine translation element. Our latest partner product, Workflow Studio, with multiple data connectors and Natural Language Processing (NLP) features, has greatly simplified the time to delivery and effort to implement often complex deployments.
While Workflow Studio may be new to our product portfolio, internally within Omniscien, this is the same set of workflow optimization components and technologies that we use in gather, process, clean and preparing billions of bilingual and monolingual sentences of data to teach our machine translation, and other artificial technologies how to “think”.
Keywords: Deep Neural Machine Translation, Deep NMT, Hybrid Machine Translation, Private Machine Translation, Secure Machine Translation, On-Premises Machine Translation, On-Site Machine Translation, Cloud Machine Translation, Secure Machine Translation, Enterprise Machine Translation, Workflow Automation, NLP, Natural Language Processing.
Professor of Computer Science
Research in Translation – What Is Exciting and Shows Promise Ahead?
The recent trend of using deep learning to solve a wide variety of problems in Artificial Intelligence has also reached machine translation – thus establishing a new state-of-the-art approach for this application. This approach is not yet settled by any means. New neural architectures are proposed and ideas coming from such diverse fields as computer vision, game playing, and speech recognition can be applied to machine translation as well.
At the practical end, we are just learning about the deployment challenges of this technology, since old methods, for example, to integrate terminology databases or domain adaptation no longer apply.
This presentation will give an overview of the latest developments in research and what this means for practical deployment.
Keywords: Machine Learning, NMT, DNMT, Deep Neural Machine Translation, SMT, Statistical Machine Translation, Hybrid Machine Translation, Data Synthesis, Data Manufacturing, Unsupervised Learning, Artificial Intelligence, Neural Networks.
The Evolving Requirements of the Localisation Industry
Hosted by Media & Entertainment Industry Alliance (MESA) and comprised of key members of MESA this panel discussion has been gathered to perform a deep dive on the rapidly changing and evolving requirements of the localization industry with respect to media and entertainment content.
The panel will explore what is driving change and how technology, automation, and tools are impacting the day to day operations of their businesses.
If you would like to present a question to the panel, please fill in the Ask Us Anything form.
AI Meets Media Media Processing and Workflows – Media Studio 2.0 Preview
Media Studio adoption has had strong growth in 2019, mostly driven by the high-quality translation outputs and control features in Media Studio 1.0. The Omniscien team had a lot of great customer feedback and has been working on some great new language processing features for the Media Studio 2.0 and a much-improved web-based subtitle editor.
During our beta period, many of the leading brands have tied the new features and given feedback. One of the extremely popular new features that we will be demonstrating is the automated Dialog Extraction and English Master Template (EMT) Creation where almost any Director’s Script and video can be paired to produce a time code EMT within minutes. We have to date processed more than 70,000 pages of scripts converting them into high-quality EMT with just a few clicks.
We have a host of other features such as automated subtitle language identification and classification, automated glossary creation for a single video episode or an entire series. This includes automated bilingual glossary creating and editing. Automated bilingual subtitle pairing to help companies organize their digital assets into multilingual collections by language and groups. These are just a few of the features we will be demonstrating with this live demo. Attendees can also sign up for a free trial of these new tools that cut cost, time and effort when working with an ever-increasing volume of media content.
Guest Speaker: Alphie Larrieu will present a case study of Astro’s experience using the latest Media Studio tools during the software beta program.
Keywords: Artificial Intelligence, AI, Machine Translation, Dialog Extraction, Automated Speech Recognition, Voice Recognition, Transcription, Productivity Gains, Best Practices, Subtitle Workflow Automation, Subtitle Management Platform, ROI, Return On Investment, Case Study, NLP, Natural Language Processing.