Human language technologies

Human language technologies

Researching software and systems that bridge the linguistic divide between people and machines to make communicating with computers as natural as speaking with family and friends.

At Microsoft, researchers in human language technologies are advancing the state of the art in natural language processing, speech recognition, dialog systems and spoken language understanding to help computers master the nuance and complexity of human communication, the currency of collaboration.

Researchers use tools and methods from machine learning, deep neural networks and other branches of artificial intelligence to close communication gaps between humans and machines. Linguistic data compiled from real-world human-human and human-computer communications is used to ground language with models of words, phrases and sentences, and to guide and train algorithms to recognize speech, process sound, and engage in meaningful dialogs.

When humans and machines speak the same language, they can do more together.

Focus areas

 

Deep learning

Neural net based methods underlie our work across scenarios in all areas of speech recognition, language generation, dialog control, and machine translation.

Speech Recognition

We develop new signal processing methods and deep learning algorithms to understand the words someone says. Our ultimate goal is to solve the cocktail party problem.

Dialog Systems

Enriching the human experience with intelligent interactive systems and technologies that are participants, agents and collaborators in open-world, multi-party conversations.

Machine Reading

Developing algorithms that allow computers to scan and understand vast amounts of textual information, for example to offer advice on medical conditions.