The document introduces SmartMATE, an all-in-one machine translation and post-editing environment. It uses statistical machine translation powered by Moses, and allows for engine creation, tuning, job management, post-editing by linguists, and QA review. The system can be hosted on Amazon Cloud, a client's data center, or Capita's own data center, and integrates various file formats. It is aimed at reducing translation turnaround times and costs for clients.
High quality machine translation short id-2706textanorg
The researchers developed a mathematical model and prototype for high-quality machine translation between English and Russian on technical topics. They propose a project to expand this to 110 language pairs on non-fiction texts at a quality comparable to a human translator. Their financial projections estimate $14 million in profit after 3 years growing to $190 million after 5 years by monetizing the "untapped market" of machine translation and attracting over 150,000 crowdsourced contributors to expand the translation domains and languages covered. They request $900,000 in investments which they expect to generate a net present value of $89.6 million and internal rate of return of 282%.
2017 will see the emergence of Machine Translation 2.0, and KantanNeural signals a giant step towards using cutting-edge technology to improve automated translation accuracy and increase productivity.
In this webinar, Tony provides an overview of KantanNeural and discuss how users can translate documents using NMT. He discusses how to evaluate the translation quality of the NMT engines with the new A/B testing feature on KantanLQR™. Dimitar briefly talks about the benefits of translating using Neural technology and the future development plans for NMT at KantanLabs.
YouTube: https://youtu.be/_2yIZxVqqmw
Interview de Martine Bocquillon pour la journée internationale des droits des...SPB
A l’occasion de la journée internationale des droits de la femme, retrouvez le parcours et les convictions à travers une interview de Martine Bocquillon, fondatrice et présidente de Point Services Mobile / Phone Service Center.
Machine translation is an easy tool for translating text from one language to another. You've probably used it. But do you know what machine translation really is? Or when you should or shouldn't use it? Navigate through this presentation to learn more!
Good Applications of Bad Machine Translationbdonaldson
The document discusses machine translation (MT) and its potential uses and improvements. It notes that MT is showing improved productivity when integrated into workflows and that some companies are using MT to translate large portions of content. The document also discusses using MT combined with human translation and search/retrieval to provide cost-effective translation of large amounts of content.
The document introduces SmartMATE, an all-in-one machine translation and post-editing environment. It uses statistical machine translation powered by Moses, and allows for engine creation, tuning, job management, post-editing by linguists, and QA review. The system can be hosted on Amazon Cloud, a client's data center, or Capita's own data center, and integrates various file formats. It is aimed at reducing translation turnaround times and costs for clients.
High quality machine translation short id-2706textanorg
The researchers developed a mathematical model and prototype for high-quality machine translation between English and Russian on technical topics. They propose a project to expand this to 110 language pairs on non-fiction texts at a quality comparable to a human translator. Their financial projections estimate $14 million in profit after 3 years growing to $190 million after 5 years by monetizing the "untapped market" of machine translation and attracting over 150,000 crowdsourced contributors to expand the translation domains and languages covered. They request $900,000 in investments which they expect to generate a net present value of $89.6 million and internal rate of return of 282%.
2017 will see the emergence of Machine Translation 2.0, and KantanNeural signals a giant step towards using cutting-edge technology to improve automated translation accuracy and increase productivity.
In this webinar, Tony provides an overview of KantanNeural and discuss how users can translate documents using NMT. He discusses how to evaluate the translation quality of the NMT engines with the new A/B testing feature on KantanLQR™. Dimitar briefly talks about the benefits of translating using Neural technology and the future development plans for NMT at KantanLabs.
YouTube: https://youtu.be/_2yIZxVqqmw
Interview de Martine Bocquillon pour la journée internationale des droits des...SPB
A l’occasion de la journée internationale des droits de la femme, retrouvez le parcours et les convictions à travers une interview de Martine Bocquillon, fondatrice et présidente de Point Services Mobile / Phone Service Center.
Machine translation is an easy tool for translating text from one language to another. You've probably used it. But do you know what machine translation really is? Or when you should or shouldn't use it? Navigate through this presentation to learn more!
Good Applications of Bad Machine Translationbdonaldson
The document discusses machine translation (MT) and its potential uses and improvements. It notes that MT is showing improved productivity when integrated into workflows and that some companies are using MT to translate large portions of content. The document also discusses using MT combined with human translation and search/retrieval to provide cost-effective translation of large amounts of content.
1. Real time bidding (RTB) refers to the practice of buying and selling display ad impressions through ad exchanges in real time and one impression at a time.
2. AWS is well suited for building RTB solutions due to its scalability, global infrastructure, and services that handle non-differentiated heavy lifting like networking and data processing.
3. Sample RTB architectures on AWS use Elastic Load Balancers and Auto Scaling Groups for front-end servers, DynamoDB and Redis for low latency caches, Kinesis and Spark for data collection and analytics, and EC2 Spot Instances to reduce costs. Building on AWS allows customers to focus on their competitive advantages rather than infrastructure.
It’s no longer a question of whether technologies will reshape language service industry; it's just a matter of how quickly and how deeply. The future of translation industry will be prosperously stimulated by the further development of economic globalization and the popularization of internet usage, but clients' requirement will be further diverse in terms of quality, turnaround, volume, content, and cost. To deliver matched services, language service providers need to enable agile translation, machine translation and scalable translation capacity. However, it is hard to deliver all these diverse services without the help of technology and an innovative business model. New technologies, such as workflow automation, online service, crowdsourcing supported by new technologies and internet becoming a competitive edge for LSPs, and new relationships with resources (translators) are also a must after millennial generation dominate the labor market, the succeed of a LSP will be more technologies- and innovations-driven. This presentation will focus on how technology/Internet is reshaping the translation industry in China.
"For-Information-Purposes-Only" translation meets the needs of a specific group of people in each country, among many others. Who are them? How localization engineering technologies can help? How big data and cloud computing can make a difference? This presentation will try to answer these questions.
This document summarizes the evolution of the translation technology landscape from the 1980s to the present and potential future trends. It covers major developments in each decade including the rise of personal computing and tools like translation memory in the 1980s and 1990s. The 2000s saw the growth of the internet, web services, and content management systems. Recent years have seen increased integration, convergence of technologies like machine translation and speech-to-speech, and a shift to cloud-based and mobile offerings. The document predicts translation may increasingly involve cultural consulting and transcreation rather than direct translation as machine translation capabilities advance.
Jaap van der Meer, Director of TAUS, shares a compilation of the feedback on the Big Idea as well as a complete overview of new TAUS features and services and new partnerships.
Pangea Machine Translation platform from Pangeanic. A product presentation by Manuel Herranz, Elia Yuste, Andi Frank showcasing the best of automated cleaning cycles, automated engine retraining, machine translation engine creation.
Hosted by Henri Broekmate (Lionbridge). Panelists Nathalie Dougall (Booking.com), Matt Romaine (Gengo), Bernie Hsu (Alibaba).
For many firms, global crowdsourcing is an unparalleled way to reduce fixed costs and dramatically enhance operating efficiency and scalability. Enterprise crowdsourcing and big data seem to be a good match, particularly as data-related work can often be broken down into tasks or projects. Managing resources and workflows at the task or unit level is at the heart of the localization industry’s expertise. Many suppliers are finding that they can easily offer adjacent services such as search relevance, sentiment analysis, data tagging, user generated content curation, transcription, and data enrichment, in a crowd model – typically in a private crowd. This panel will discuss whether localization service providers and language technology innovators are offering relevant crowd solutions. Using technology as a lens, we will also discuss whether there is a role for increased crowdsourcing as the adoption of MT drives increased post-editing work. Lastly we will exchange ideas about where the crowdsourcing opportunity sits in the framework of the “gig” economy, and whether it will thrive and grow, or crumble under the push for legislation and labor reform.
TAUS Roundtables are one-day meetings for buyers and providers of language services and technologies, aimed at an open exchange about language business innovation and translation technology. These industry brainstorming sessions are organized in various cities around the world, supported by TAUS members and regional partners.
The format of TAUS Roundtable is open and informal. The goal is to learn from your peers in the industry. Participants may present their experience and perspective on a particular question and request others in the meeting to share their reflections.
This document summarizes a presentation about using AWS for digital transformation. It discusses how customers now expect personalized, digital experiences anytime and anywhere. It also notes that organizations often fail to fully transform when adopting new technologies by not addressing cultural and organizational changes. The presentation then describes how a company called LocalCover built their architecture on AWS to create a global, cross-border warranty product using microservices and serverless technologies like Lambda. It emphasizes starting small and combining best of breed cloud solutions.
The translation industry has undergone a paradigm shift every decade since 1980, but none was as big as the one we are facing now. We are entering the Convergence era: automatic translation will be a utility embedded in every app, device, sign board and screen. Businesses will prosper by finding new customers in new markets. Governments and citizens will connect and communicate easily. Consumers will become world-wise, talking to everyone everywhere as if language barriers never existed. It will not be perfect, but it will open doors and break down barriers. And it will give a boost to the translation industry, which will be chartered to constantly improve the technology and fill the gaps in global communications. In this interactive opening session Jaap van der Meer zooms in on the choices we are facing and the decision factors that help us make planning for an uncertain future opportunistic and profitable.
This presentation is a part of the MosesCore project that encourages the development and usage of open source machine translation tools, notably the Moses statistical MT toolkit. MosesCore is supported by the European Commission Grant Number 288487 under the 7th Framework Programme.
For the latest updates go to http://www.statmt.org/mosescore/
or follow us on Twitter - #MosesCore
Overcoming Today's Data Challenges with MongoDBMongoDB
The document outlines an agenda for an event hosted by MongoDB on October 3rd 2017 in Amsterdam on overcoming data challenges with MongoDB. The agenda includes presentations on how the world has changed since relational databases were invented, how to transform IT environments with MongoDB, MongoDB use cases, and a customer story from IHS Markit. There will also be a Q&A session and conclusion. Speakers include representatives from MongoDB and IHS Markit.
Amazon began as an online bookstore and has since diversified into many other product lines and services to become the world's largest online retailer. It generates sales from both retail and non-retail operations. Amazon faces high competition but also has significant competitive advantages from economies of scale, its expertise in technology, and talented workforce. The document analyzes Amazon's business strategy, industry environment, and strategic alternatives to expand further into high growth areas like cloud computing services while maintaining its low cost leadership.
Nov 2019 kafka with mongo db and confluent sydneyAndrew Blades
This document summarizes a meetup event about architecting for innovation with MongoDB, Kafka, and Confluent. It includes presentations from Sam Harley of MongoDB on powering microservices with Kubernetes, Kafka and MongoDB, and from Brett Randall of Confluent on building consciousness on real time events using KSQL recipes. The meetup concludes with a door prize drawing and announcement of the next meetup in December.
Presenter: Josef Kubovský // CEO // Nimdzi Insights
The language service industry is evolving rapidly, especially since the pandemic changed the world as we know it. Are these changes critical? Do we need to panic? Are we missing out on something? This session will touch upon different segments of our industry and share the latest trends to start a broader conversation with the Plunet Summit audience.
MiTiN 2013 Keynote in Detroit MichiganKirti Vashee
The document discusses how the role of the translator is changing due to a massive increase in the volume of content needing translation as well as faster turnaround times and lower costs. This has led to a greater reliance on machine translation and post-editing workflows over traditional translation workflows. The summary also notes that content is becoming more dynamic, social, and customer-focused which is further impacting translation needs and processes.
6. Entrepreneurship - Juan Jose Arevalillo Doval (Hermes)RIILP
This document discusses the translation industry, including its size, standards, and various roles within it. It describes translation as both a product and service. The industry is large but also faces issues like margin reductions and low-cost competition. There are various paths one can take to enter the industry, whether as a freelancer or employed translator within a translation company, agency, or other organization. Quality, costs, and time are three important factors for managing translation projects and the industry overall.
The document introduces the Dynamic Quality Framework (DQF), which aims to standardize quality measurements across the translation industry. It describes DQF as inclusive, industry-shared, and data-informed. The framework integrates with common CAT tools and TMS through open APIs to collect translation and review data and provide interactive dashboards and reports for performance tracking and benchmarking at the project and organizational level.
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1. Real time bidding (RTB) refers to the practice of buying and selling display ad impressions through ad exchanges in real time and one impression at a time.
2. AWS is well suited for building RTB solutions due to its scalability, global infrastructure, and services that handle non-differentiated heavy lifting like networking and data processing.
3. Sample RTB architectures on AWS use Elastic Load Balancers and Auto Scaling Groups for front-end servers, DynamoDB and Redis for low latency caches, Kinesis and Spark for data collection and analytics, and EC2 Spot Instances to reduce costs. Building on AWS allows customers to focus on their competitive advantages rather than infrastructure.
It’s no longer a question of whether technologies will reshape language service industry; it's just a matter of how quickly and how deeply. The future of translation industry will be prosperously stimulated by the further development of economic globalization and the popularization of internet usage, but clients' requirement will be further diverse in terms of quality, turnaround, volume, content, and cost. To deliver matched services, language service providers need to enable agile translation, machine translation and scalable translation capacity. However, it is hard to deliver all these diverse services without the help of technology and an innovative business model. New technologies, such as workflow automation, online service, crowdsourcing supported by new technologies and internet becoming a competitive edge for LSPs, and new relationships with resources (translators) are also a must after millennial generation dominate the labor market, the succeed of a LSP will be more technologies- and innovations-driven. This presentation will focus on how technology/Internet is reshaping the translation industry in China.
"For-Information-Purposes-Only" translation meets the needs of a specific group of people in each country, among many others. Who are them? How localization engineering technologies can help? How big data and cloud computing can make a difference? This presentation will try to answer these questions.
This document summarizes the evolution of the translation technology landscape from the 1980s to the present and potential future trends. It covers major developments in each decade including the rise of personal computing and tools like translation memory in the 1980s and 1990s. The 2000s saw the growth of the internet, web services, and content management systems. Recent years have seen increased integration, convergence of technologies like machine translation and speech-to-speech, and a shift to cloud-based and mobile offerings. The document predicts translation may increasingly involve cultural consulting and transcreation rather than direct translation as machine translation capabilities advance.
Jaap van der Meer, Director of TAUS, shares a compilation of the feedback on the Big Idea as well as a complete overview of new TAUS features and services and new partnerships.
Pangea Machine Translation platform from Pangeanic. A product presentation by Manuel Herranz, Elia Yuste, Andi Frank showcasing the best of automated cleaning cycles, automated engine retraining, machine translation engine creation.
Hosted by Henri Broekmate (Lionbridge). Panelists Nathalie Dougall (Booking.com), Matt Romaine (Gengo), Bernie Hsu (Alibaba).
For many firms, global crowdsourcing is an unparalleled way to reduce fixed costs and dramatically enhance operating efficiency and scalability. Enterprise crowdsourcing and big data seem to be a good match, particularly as data-related work can often be broken down into tasks or projects. Managing resources and workflows at the task or unit level is at the heart of the localization industry’s expertise. Many suppliers are finding that they can easily offer adjacent services such as search relevance, sentiment analysis, data tagging, user generated content curation, transcription, and data enrichment, in a crowd model – typically in a private crowd. This panel will discuss whether localization service providers and language technology innovators are offering relevant crowd solutions. Using technology as a lens, we will also discuss whether there is a role for increased crowdsourcing as the adoption of MT drives increased post-editing work. Lastly we will exchange ideas about where the crowdsourcing opportunity sits in the framework of the “gig” economy, and whether it will thrive and grow, or crumble under the push for legislation and labor reform.
TAUS Roundtables are one-day meetings for buyers and providers of language services and technologies, aimed at an open exchange about language business innovation and translation technology. These industry brainstorming sessions are organized in various cities around the world, supported by TAUS members and regional partners.
The format of TAUS Roundtable is open and informal. The goal is to learn from your peers in the industry. Participants may present their experience and perspective on a particular question and request others in the meeting to share their reflections.
This document summarizes a presentation about using AWS for digital transformation. It discusses how customers now expect personalized, digital experiences anytime and anywhere. It also notes that organizations often fail to fully transform when adopting new technologies by not addressing cultural and organizational changes. The presentation then describes how a company called LocalCover built their architecture on AWS to create a global, cross-border warranty product using microservices and serverless technologies like Lambda. It emphasizes starting small and combining best of breed cloud solutions.
The translation industry has undergone a paradigm shift every decade since 1980, but none was as big as the one we are facing now. We are entering the Convergence era: automatic translation will be a utility embedded in every app, device, sign board and screen. Businesses will prosper by finding new customers in new markets. Governments and citizens will connect and communicate easily. Consumers will become world-wise, talking to everyone everywhere as if language barriers never existed. It will not be perfect, but it will open doors and break down barriers. And it will give a boost to the translation industry, which will be chartered to constantly improve the technology and fill the gaps in global communications. In this interactive opening session Jaap van der Meer zooms in on the choices we are facing and the decision factors that help us make planning for an uncertain future opportunistic and profitable.
This presentation is a part of the MosesCore project that encourages the development and usage of open source machine translation tools, notably the Moses statistical MT toolkit. MosesCore is supported by the European Commission Grant Number 288487 under the 7th Framework Programme.
For the latest updates go to http://www.statmt.org/mosescore/
or follow us on Twitter - #MosesCore
Overcoming Today's Data Challenges with MongoDBMongoDB
The document outlines an agenda for an event hosted by MongoDB on October 3rd 2017 in Amsterdam on overcoming data challenges with MongoDB. The agenda includes presentations on how the world has changed since relational databases were invented, how to transform IT environments with MongoDB, MongoDB use cases, and a customer story from IHS Markit. There will also be a Q&A session and conclusion. Speakers include representatives from MongoDB and IHS Markit.
Amazon began as an online bookstore and has since diversified into many other product lines and services to become the world's largest online retailer. It generates sales from both retail and non-retail operations. Amazon faces high competition but also has significant competitive advantages from economies of scale, its expertise in technology, and talented workforce. The document analyzes Amazon's business strategy, industry environment, and strategic alternatives to expand further into high growth areas like cloud computing services while maintaining its low cost leadership.
Nov 2019 kafka with mongo db and confluent sydneyAndrew Blades
This document summarizes a meetup event about architecting for innovation with MongoDB, Kafka, and Confluent. It includes presentations from Sam Harley of MongoDB on powering microservices with Kubernetes, Kafka and MongoDB, and from Brett Randall of Confluent on building consciousness on real time events using KSQL recipes. The meetup concludes with a door prize drawing and announcement of the next meetup in December.
Presenter: Josef Kubovský // CEO // Nimdzi Insights
The language service industry is evolving rapidly, especially since the pandemic changed the world as we know it. Are these changes critical? Do we need to panic? Are we missing out on something? This session will touch upon different segments of our industry and share the latest trends to start a broader conversation with the Plunet Summit audience.
MiTiN 2013 Keynote in Detroit MichiganKirti Vashee
The document discusses how the role of the translator is changing due to a massive increase in the volume of content needing translation as well as faster turnaround times and lower costs. This has led to a greater reliance on machine translation and post-editing workflows over traditional translation workflows. The summary also notes that content is becoming more dynamic, social, and customer-focused which is further impacting translation needs and processes.
6. Entrepreneurship - Juan Jose Arevalillo Doval (Hermes)RIILP
This document discusses the translation industry, including its size, standards, and various roles within it. It describes translation as both a product and service. The industry is large but also faces issues like margin reductions and low-cost competition. There are various paths one can take to enter the industry, whether as a freelancer or employed translator within a translation company, agency, or other organization. Quality, costs, and time are three important factors for managing translation projects and the industry overall.
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The document introduces the Dynamic Quality Framework (DQF), which aims to standardize quality measurements across the translation industry. It describes DQF as inclusive, industry-shared, and data-informed. The framework integrates with common CAT tools and TMS through open APIs to collect translation and review data and provide interactive dashboards and reports for performance tracking and benchmarking at the project and organizational level.
The document discusses the evolution of machine translation (MT) technology over time from early conceptual ideas to modern neural machine translation (NMT) systems. It uses metaphors of a band changing their sound over time by adding new band members, such as an "MT guy", to represent how translation companies can adapt to new technologies. The presentation encourages translation businesses to thoughtfully integrate new tools like NMT by involving stakeholders and focusing on people in the process of transition.
The document summarizes the results of a machine translation evaluation that compared human and machine translations. Several human and machine translation systems were evaluated on a test set containing sentences translated between English and Chinese. The top performing systems were combinations of human and machine translations. There was criticism of claims of machine translation achieving "human parity" due to limitations in the test set only using sentences rather than documents, and evaluators not being qualified translators. Neural machine translation systems are argued to have advantages over statistical and rule-based systems by processing full sentences and storing additional context in hidden layers.
The document discusses how artificial intelligence and neural machine translation will change the role of human translation over time. While AI can handle the translation process at scale, humans will still be needed for local knowledge, problem solving, and tasks like optimizing processes, improving output quality, and ensuring quality. However, a fragmented technology landscape slows businesses down. The solution proposed is an integrated localization hub that connects content systems, translation technology, and translation services through a single API to address current issues where technical knowledge and system fragmentation are still barriers.
As contents published on the Internet are becoming more and more dominated by videos, requirements on the language translation have also changed. Specifically, video publishers and distributors have a significant interest in balancing both the translation time and the accuracy. To this end, Pactera has invested in solutions, which leverage machine translation to reduce the overall translation time, and recruit human translators to improve the accuracy in a Wikipedia-like fashion. At Pactera, we aim to help video contents to reach billions of people that were not possible before.
The document discusses innovation in machine translation and language technology. It notes that translation is becoming more data-driven and algorithmic, with machines learning from large amounts of data. It also mentions that translation may become invisible and automated like utilities such as electricity. The document then lists some concepts characterizing innovative contest candidates in game changer awards, such as advanced machine translation, artificial intelligence, and automated quality evaluation. Finally, it states that six contestants will each have six minutes to pitch their innovative ideas.
Review processes as the last step in quality assurance workflows are “notorious for causing delays and frustrations”. The reason normally is a flawed process: Many manual steps for the PMs, the lack of intuitive, layout-oriented collaboration software, plus the expectation of review to “fix a broken translation” in the last second rather than giving strategic process input. globalReview shifts this paradigm: As an integrated, collaborative platform with full layout editing it provides a positive review experience. At the same time, it pushes quality upstream applying DQF principles: Flexible content profiles define precise quality expectations; issue categories and scoring effectively gauge and also track translation quality over time; a sampling module allows for fast yet accurate quality evaluation. Put together, this allows the customer to raise the process from painful review to strategic quality management and gain valuable business intelligence.
A global P2P Trading Platform for TMs will be introduced. Tmxmall TM marketplace is the core, and client TM software and CATs are the input and output respectively. User of CATs is able to search the TMs of client users while it does not require client users to upload TMs to the cloud.
The presentation will introduce the NLP technologies used in Shiyibao and the main product features, covering the following points:
Function of giving automatic grades for translations based on translation quality automatic evaluation algorithm;
Function of giving automatic comments based on rules matching;
Function of sorting translations according to their similarity or some specific fragments to dramatically improve the efficiency of reviewing and commenting on translations.
In today’s digital economy, content is becoming smaller, more fragmented, and in need of on-demand translation in minutes and around the clock. Traditional localization models are no longer sufficient in meeting these always-on, agile, fast, and small translation requirements of the digital age. This is why mobile translation services like Stepes that are able to deliver quality, speed, and scalability are poised to see tremendous growth. During this 6-minute presentation, Stepes will demonstrate live its instant human translation service for micro content. Powered by human translators from around the world, Stepes is the world’s first mobile translation ecosystem delivering quality translation services using a networking model similar to Uber and Lyft.
This document discusses TruTran's open machine translation platform and the trends in machine translation engine development. It notes that neural network technology allows each company to have its own customized trained neural machine translation engine. The open source nature of neural networks means that machine translation will be "generalized" or available to more users. However, enterprises currently lack professionals skilled in natural language processing and training data can be difficult to process. TruTran's platform aims to address these issues by allowing users to easily upload custom training data and corpora, select a domain to train an engine, and have the engine trained within 6 days on the platform's resources. This gives each company their own commercial-grade machine translation engine at low cost and with their
Kirk Zhang, the COO of Wiitrans, presented on their semantic matching and translator resource management tools which aim to deliver high quality translations by matching content to appropriate translators based on their individual translator profiles and histories. The tools analyze translator-specific language assets, glossaries, and translation memories to best match work to translators and simplify the translation process.
The document describes a computer-aided translation and interpretation training system called CATS. It provides course management, multi-lingual resource centers, and translation management platforms to support online translation and interpretation courses. CATS allows instructors to upload multimedia content and documents, create translation cases and assignments, and evaluate student work. It aims to improve over traditional methods of collecting assignments through email by offering an integrated online platform for pre-class, in-class, and post-class activities.
The document announces a Translation Technology Showcase event hosted by TAUS on February 28, 2017 in Shenzhen. The event will feature presentations from various translation technology companies on topics like multichannel translation for the digital economy, using free and open source tools, leveraging large translation memories, and neural machine translation. The agenda lists out the scheduled presentations and their times. The document also mentions that TAUS recently published an updated Translation Technology Landscape Report covering trends in the industry and profiles of over 80 companies.
Most of LSPs have not converted the translated bilingual documents to TM till now. Even the LSPs have established TMs, they are also confronted with disordered management of TMs and low efficiency. This report will share the way of quick TM establishment with Tmxmall Cloud-Based Smart Aligner, the way of Management of large-scale TMs with Private Cloud-Based TM for achieving pre-translation with large-scale TMs and team cooperation and etc.. Besides, the report will introduce Tmxmall TM marketplace, which is expected to promote TM sharing. Finally, we will share the experience of LSPs on alignment and Private Cloud-Based TM management for reducing translation costs and increasing profits.
SDL is the leader in global content management and language translation solutions. With more than 20 years of experience, SDL helps companies build relevant online experiences that deliver transformative business results on a global scale. Translation Industry continues to grow, and Freelancers, LSPs and Corporate clients all see increased demand as more and more content is created, so we have to address them all. As a Market-leading translation productivity tool, SDL Trados Studio is trusted by over 200,000 translation professionals to boost productivity, control quality and aid collaboration. SDL has launched Trados Studio 2017. This presentation will introduce SDL Trados Studio 2017 and highlight SDL’s new productivity booster- UPLIFT, which is well welcomed by global clients.
This document discusses Lingosail's translation technology products and services, including machine translation, corpus construction, and translation services. It outlines how Lingosail's machine translation process editing (MTPE) solutions can provide easier entry into translation for clients, higher translation efficiency, and more scalable management of translation workflows. The document also describes Lingosail's patent post-editing training course for translators, which saw hundreds of participants last year, and resulted in trainees increasing their translation speed and quality after training.
This document discusses how to introduce machine translation (MT) into a company to improve localization processes. It outlines challenges with the current process of 30 localization loops involving 40 translators across different locations with no quality or cost control. Introducing MT for display text localization could speed up availability, lower costs by 25%, and reduce unnecessary translation loops by 50%. A short-term goal is to use MT for development phases with a final quality loop involving human translation and post-editing. Long-term preparation is needed to expand MT use while addressing risks, quality guidelines, and system environments.
This document discusses integrating XTM Cloud and TAUS DQF to enable higher quality translation projects. Key steps include creating accounts in both systems, configuring LQA parameters and issues in XTM, creating translation projects in XTM with LQA steps, performing translations and LQA reviews in XTM, and then viewing productivity and quality results in the TAUS DQF system. The integration is meant to provide benefits like higher productivity, improved quality, and better data to evaluate machine translation systems.
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1. Market Shifts and
Technology Disruption
BeGlobal
Brian Otis (botis@sdl.com)
TAUS Translation Technology Showcase Webinar
November 13, 2013
2. Agenda
• Shifts in the Translation Market
–Explosion of content volume and types demands new models
–Technology will disrupt and facilitate new models
• SaaS, Crowdsourcing, MT, etc.
• New models help enterprises of all sizes “Maximize
the ROI on their translation budgets”
• Example: SDL Beglobal
4. Alignment Has Evolved Between Translation Customers and
Providers Based on Enterprise Size
G2000
Enterprise Customer: Premium LSP
• Highest quality translation
• Highest quality service
• Require high volume to get LSP’s attention
• Translation volume limited by investment
Midmarket
(Millions)
Prosumer (100s Millions)
SMB/Mid-market: Midmarket LSP
(wide range)
• Volume varies greatly
• Still focused on high quality translation
• Delivery models vary to align costs
• Many prospects go without
Everyone else: on-line LSP
• Low volume
5. Translation Requirements are Changing
With the explosion of content volume and content types…
…organizations of all sizes have requirements for multiple
translation quality/cost points
… lower willingness(ability) to spend based on ROI, shelf life,
etc..
The key is to maximize the ROI your translation budget by…
…applying the optimal translation quality/price option to
each content type
6. ROI on Translation Varies by Content Type
Premium
Quality and
Service
6
High Quality,
Lower Touch
Low - mid Quality
Machine
Translation
7. Aligning Content Type, Translation Requirements and ROI
Content type
Highest Value,
brand defining
content
Important content
but high volume or
low budget
Lower value
content
Large volume
and/or real time
turnaround
Quality
Requirement
Translation
“Types”
Content Volume
Very High
Low
Premium Quality
and Service
High
Varies
High Quality,
Lower Touch
Varies
Usually High
Low-Mid Quality
Low
Very high (or realtime requirements)
Machine
Translation
Quality
8. Provider Landscape and Evolving Models
Provider
Segment
Machine
Translation
Low - mid
Quality
High Quality,
Lower Touch
SDL, Lionbridge, Transperfect,
STAR Group (CH), Euroscript
(Lux), WeLocalize (US), BigWord
(UK), etc.
Enterprise
LSPs
Self-service
LSPs
(on-line)
Leverage
Technology
Rev.com, Gengo,
Verbingo, OHT,
getlocalization,
Qordoba,
Textmaster,
VerbalizeIT, etc.
Crowdsourced
Translation
Providers
(on-line)
MT providers
Premium Quality &
Service
SDL BeGlobal,
Google, Bing,
Moses, Systran,
ProMT, etc.
OHT, C2T, Srtraker,
Fox Translation,
Tolingo, Speaklike,
Babylon,
LiveTranslation, etc.
Leverage
Technology
Leverage
Technology
Leverage
Technology
• Company positioning vary, some providers provide multiple translation models
• Translation outcome providers only, software providers not included
9. Today – Limited Supply of Lower Cost Translation Options
Limits Demand & Limits Market Growth
Translation
“types”
Today’s
Constraints
Prosumer
Access to
Supply
Machine
Translation
Translation Coverage with current approaches
Cost Limits
Demands
Low-mid
Quality
G2000
Cost Limits
Demand
High Quality,
Lower Touch
Mid-market
Premium
Quality and
Service
Quality Limits
Demand
10. Tomorrow – Aligning Translation ROI by Content Type Leads
to Translation Explosion
Translation
“types”
Tomorrow’s
Solutions
Prosumer
Technology
Drives Cost
Down
(accessibility)
Low-mid Quality
G2000
Cost Always
Limits Demand
High Quality, Lower
Touch
Mid-market
Premium Quality
and Service
Technology
Increases Access
to Supply
Improved Quality
Machine Translation Drives Demand
Increasing volumes
Increasing value of technology leverage
Translation Coverage with NEW approaches
11. SDL BeGlobal Language Cloud Platform
Baseline Machine
Translation
MT
Content for
Translation
API
Trained Machine
Translation
Standard Professional
Translation
WEB
PT
Verified Professional
Translation
Specialized
Professional
Translation
Premium Professional
Translation
Translated
Content
13. Summary
• Shifts in the Translation Market
–Explosion of content volume and types demands new
models
–Technology will disrupt and facilitate new models
• SaaS, Crowdsourcing, MT, etc.
• New models help enterprises of all sizes “Maximize
the ROI on their translation budgets”
• Example: SDL Beglobal