Abstract: AI has a broad range of use cases in operations, production, and supply chain management. However, it is in front-end functions, such as sales and customer support, where organizations are reaping the most rewards from AI. As our world becomes more digital, conversational AI is being used to enable communication between computers and humans. The global reach of business has given rise to a need to train data for AI systems that understand text and speech in multiple languages.
Conversational AI is complex and requires the expertise of developers, data scientists, and when a truly global customer experience is required, linguists. A multilingual chatbot or voice assistant adds a layer of intricacy, given the volume and creation of data needed for ingestion into the machine learning systems required to meet the linguistic requirements and ensure all business and cultural realities are met.
From languages, dialects, and accents to sarcasm, emojis, and slang, there are a lot of factors that can influence—and enhance—the communication between a human and a machine. Conversational AI systems need to keep up with what’s normal and what’s the ‘new normal’ with human communication.
In this session, Olga Beregovaya, VP, AI Innovation at Welocalize, Inc., will cover the business benefits of conversational AI, training data to deliver conversational AI in multiple languages, and how to enhance global customer experience.
- The different types of conversational AI and chatbots
- Business benefits of conversational AI
- Training data for AI systems that understand text and speech in multiple languages
Bio: A seasoned professional with over 20 years of leadership experience in language technology, NLP, ML, localization, and AI data generation and annotation, Olga is the VP, AI Innovation at Welocalize. She is passionate about growing business through driving change and innovation, and an expert in building things from scratch and bringing them to measurable success. Olga has experience on both the buyer and the supplier side, giving her unique perspective around establishing strategic buyer/supplier alliances and designing cost-effective Global Content Lifecycle Programs. She has built and managed global production, engineering and development teams of up to 300 members specializing in MT and broader NLP.