Partners with Carnegie Mellon University, INESC-ID and Instituto de Telecomunicações to Develop Research on Multilingual AI Agent Assistants (MAIA)
San Francisco, Calif. and Lisbon, Portugal Unbabel, the AI-powered, human-refined translation platform that enables multilingual customer service at scale, announced today that the company’s AI research team is partnering with Carnegie Mellon University, INESC-ID, and Instituto de Telecomunicações to dramatically improve multilingual conversational chat. The MAIA: Multilingual AI Agent Assistants large scale research project will augment customer service agents with AI, making it more efficient for enterprises to deliver chat in 30 languages and improve customer satisfaction through human empathy.
“While chat is becoming one of the preferred means for customer service, it currently faces important limitations that revolve around supporting customers in their native language to drive better customer satisfaction, while maintaining the human-to-human experience,” said Andre Martins, vice president of AI research at Unbabel. “The MAIA research project will enable customer service and support professionals to capture context and establish empathy with customers by infusing a machine and human approach, making the process more seamless and accurate.”
Over the course of 36 months, the research team proposes to build a toolbox of machine learning technologies for online multilingual customer service, which includes context-aware machine translation, automatic answer generation, and conversational quality estimation. This will significantly expand the current portfolio of Unbabel AI technologies, creating a new model: an agent assistant that will facilitate the communication between human agents and international customers, making live chat customer service platforms more multilingual, scalable and capable of ensuring higher customer satisfaction. It will also help agents with new dialogue-oriented productivity tools, and expand Unbabel’s renowned quality estimation technology to assess conversational quality.
“As the global economy becomes even more connected, it is more important than ever to be able to communicate effectively across cultural borders,” said Graham Neubig, associate professor at Carnegie Mellon University. “Tackling this task through machine translation is challenging due to the need to consider relevant conversational context in order to generate precise, polite, and culturally appropriate translations. At the same time, the interactive nature of conversations poses a number of new opportunities for translation technology. The MAIA project will advance natural language processing (NLP) and machine learning technology to tackle these challenges and opportunities, increasing the speed, quality, and user experience of multilingual machine-mediated conversations.”
In addition to MAIA, Unbabel’s research team is embarking and leading on the following research: Scribe: Partnering with INESC-ID, this project aims to develop a technical solution for automatic transcription, translation and subtitling of audiovisual contents. This solution combines the benefits of AI with the quality provided by a community of human editors. Unbabel4EU: This project aims to build an advanced European language engine for borderless business communication to create Europe’s translation layer. Specifically, by enabling seamless human-quality translation between any pairing of the 24 official languages of the EU in different content types (including email and chat). This project uses pivoting/triangulation models, techniques and algorithms as a method to provide translation between all the different EU official languages. It uses English, French and German as languages pivots between all the other language pairs.
For more highlighted research and publications led by Unbabel’s research team, please visit: https://unbabel.com/research/.
About Unbabel: Unbabel removes language barriers by blending advanced artificial intelligence with real time, human translations. The company’s enterprise translation platform enables customer-centric brands to provide multilingual customer service and experience at scale – delivering native-quality translations quickly, efficiently and smarter over time. It transforms customer contact centers from a cost to profit center, providing automated translation, quality estimation, human expertise and CRM integrations. With the mission to become the World’s Translation Layer, Unbabel works with leading brands such as Facebook, Microsoft, Booking.com and Uber, to make their customers happier and their support operations more efficient. For more information visit www.unbabel.com.
Media Contact: Melissa Cohen Unbabel Head of Communications comms@unbabel.com
