Global Services for Machine Intelligence

Organizations are developing intelligent systems to enhance human experiences anywhere, whether in the home, car or at work. Developers of these conversational interfaces to virtual assistants and other products require massive amounts of high quality training data and actionable user experience feedback on a global scale to make their solutions more natural, accurate, relevant and intuitive.

This is a significant challenge that Lionbridge solves with linguistic and data operations that generate high quality global data to train the systems. We combine that with global user experience testing, gathering feedback to continually improve on the human experience with these new intelligent systems.

Lionbridge provides the human component to complement and augment our customers’ AI efforts by providing scalable and complete global coverage. As customers move quickly to solve data problems, they can rely on Lionbridge to offload the program management and operational requirements to execute solutions. We align fully with our clients’ organizational structures, processes, and systems and have over a decade of exceptional performance working on the most sensitive client programs.

Our Services

Linguistic & data operations

Lionbridge provides the highest quality data to meet the exacting standards of our clients to train intelligent systems. We do this through a rigorous recruitment and screening process as well as a mature quality assurance process and system. We work both on client systems for large scale, highly secure needs and on our own tools as needed. 

Our Linguistic Operations help you develop more intuitive natural language interfaces. They include:

  • Grammatically correct phases of spoken sentences or written text
  • Consistency checking (capitalization, spelling, proofreading, etc.)
  • Translation of spoken words or written text
  • Transliteration of words and phrases

Our Data Operations provide you with cleaner input data for training engines. They include:

  • Data collection: the capture and recording of speech, written text, image or video samples
  • Data processing and engineering
  • Transcription of spoken recordings
  • Labeling and annotation of text, spoken language and videos (text, images, audio or video)
  • Scrubbed and vetted data for your recognition and search engines
  • Articulation of grammar rules in any particular language
  • Domain-specific dictionaries and ontologies

Linguistic staffing

Lionbridge provides the expertise our clients need including linguists, phoneticians, transcriptionists, translators, raters and user experience managers.

These resources are deployed to meet each client’s requirements whether that be remote, on-site, or in a Lionbridge office.

User experience testing

Understanding how people around the world experience these new intelligent systems in their home and car is critical for the success of new interface experiences.

Lionbridge provides a virtual, global network of resources that can be segmented by locales and demographics to provide feedback and insight on new products, algorithms, features and languages. Whether in the cloud or in an office, we have the flexibility and infrastructure to deploy testing labs near-site to our clients’ R&D facilities – a common need for automotive infotainment systems.

We also manage the secure distribution of pre-launch hardware into markets to test under non-disclosure agreements.

case study

Machine Intelligence: Case Study


One of the world’s largest software providers came to us for help with their internet-based maps. Used by billions of users globally, these maps display the names of the billions of locations around the world. From continents, countries, and names of capitals down to names of the smallest villages and creeks in every country.

This software company wanted to take all the map locations around the world and localize them from and into several languages so each user could read location names in their own language and writing system. Easy to do with a team of human translators...but very expensive and time consuming.

Conventional machine translation solutions can provide a cheaper alternative to human localization, but they are not designed to deal with map localization conventions in an appropriate way. This can result in low quality localization.

Localizing map locations is similar to other proper name localization where, for example, “Miller” in “John Miller” is not translated into the Russian or Chinese words for “miller.” Instead it’s written to allow a Russian or Chinese speaker to pronounce the name similar to how “Miller” is pronounced. This type of conversion where the pronunciation rather than the word meaning is preserved is called transliteration.

We developed a machine learning solution, a transliteration engine that took map localization conventions into account and enabled high-quality automatic localization of map locations. The transliteration engine enabled us to limit the role of the human translators to just review and correct the machine output, instead of doing the localization manually.

In automatic evaluation we achieved between 41-77% completely correct transliterations, when compared to human “gold” standard. But manual review of these figures revealed that the majority of the “errors” could actually be considered acceptable variants.

Overall, the introduction of the transliteration engine into the map localization workflow increased the throughput of localized terms significantly. This lead to cost savings per localized entity by turning what before was a pure localization task to one that was simply a review process. The result was faster scaling to new languages and locations.

Lionbridge Blog | See all blogs
Neural Machine Translation: How Artificial Intelligence Works When Translating Language

"After all, as data volumes and technology advancements increase, so does translatable material. But what exactly is NMT, and how does it increase localization efficiency?"

Neural Machine Translation: How Artificial Intelligence Works When Translating Language 2/17/2017