{"id":170147,"date":"2008-12-17T11:20:26","date_gmt":"2008-12-17T11:20:26","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/understand-users-intent-from-speech-and-text\/"},"modified":"2019-08-19T15:33:37","modified_gmt":"2019-08-19T22:33:37","slug":"understand-users-intent-from-speech-and-text","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/understand-users-intent-from-speech-and-text\/","title":{"rendered":"Understand User’s Intent from Speech and Text"},"content":{"rendered":"

Understanding what users like to do\/need to get is critical in human computer interaction. When natural user interface like speech or natural language is used in human-computer interaction, such as in a spoken dialogue system or with an internet search engine, language understanding becomes an important issue. Intent understanding is about identifying the action a user wants a computer to take or the information she\/he would like to obtain, conveyed in a spoken utterance or a text query.<\/p>\n

In this project, we develop robust data-driven technologies applicable to different domains, make them more practical by leveraging large amount of unlabeled data via unsupervised\/semi-supervised machine learning; by innovating machine learning algorithms that work better with less data or mismatched data; and by augmenting statistical models with domain knowledge obtained in a semi-supervised fashion. Research activities fall into the following areas:<\/p>\n