Conversational Interaction for Business
Several market studies are estimating an impressive growth of different areas and applications of language technology focused on the improvement of man-machine voice-based interfaces. Even if is difficult to draw clear technological or functional borders between Spoken Dialogue Systems, Intelligent Virtual Assistants, ChatBots, or Conversational Interfaces, all these approaches share the demand of high-quality Speech Recognition, Natural Language Understanding, Dialogue Management, Language Generation and Speech Synthesis.
However, and despite decades of research and development, building such systems is still a major challenge for the academy and the industry. The statistical approach (based on different machine learning techniques) is substituting progressively techniques based on finite-states, frame-based schemes or in general the hand-crafted dominant model for building dialogue systems for industrial applications. Partially Observable Markov decision problem (POMDP), Reinforcement Learning and more recently Deep Learning can be named among the key techniques that have proved a breakthough in this field.
In this talk I will present the key motivations, design constraints and functional goals being applied on the Fluency project. Fluency is a framework currently under development by the Lekta company. Our main goal is to build a hybrid architecture integrating the most advanced research achievements as well as ensuring critical business requirements such as dialogue control and optimization, business intelligence integration, reliability and scalability.