Data Centric Computing and User Experience

The Data Centric Computing and User Experience team at MSRA is dedicated to the research and development of data-centric applications and user experience for future data-driven and Internet-driven software and services.

In the era of information explosion and evolution of the Web, it is becoming increasingly common and vital for software and service providers to collect vast amount of customer data such as system log data, customer feedback and the Internet. Efficient use of the information is critical to improving the quality of the service and delivering superb user experience.

Natural language

The information era has brought us vast amounts of digitized text that are generated, propagated, exchanged, stored, and accessed through the Internet everyday all over the world. The accumulation of this data is making information acquisition increasingly difficult with language becoming a critical obstacle to growth. To overcome these difficulties, the Natural Language Computing (NLC) Group is focusing its efforts on a variety of research topics including multi-language text analysis, machine translation, cross language information retrieval, and question answering. Over the years, the group has made significant contributions to Microsoft products including a Japanese and Chinese Input Method Editor (IME), English writing assistant for Office 2007, Chinese couplet game for Windows Live, Chinese word breaker, pinyin search and search speller for the MSN search engine, text mining for SQL Servers and Sharepoint, and meta data extraction for MSN. Our research achievements have been published at most prestigious NLP conferences including 19 papers at ACL and 7 papers at SIGIR, from 2000-2006.

Speech

Using speech to communicate continues to be the most natural and the easiest way to exchange ideas and thoughts. However, it becomes a new game when we need to communicate with machines like computers. At MSR Asia, the Speech Group is working to make the speech chain smooth and robust when there is a machine inside the chain. We work to develop spoken language technologies, enable human-computer voice interaction, and enrich human-to-human voice communications.

The group's current focus includes automatic speech recognition to enable computers to facilitate access to data, help create content, and perform tasks; speech synthesis to enable computers to speak with a human-sounding voice, to respond and provide information, and to read; spoken-document retrieval and processing to enrich communication between people, like converting voice-mail into text; signal processing to improve the conditioning of signals, change speech signal parameters like pitch, speaking rate, voice characteristics seamlessly. Extension of statistical learning algorithms developed in speech to other pattern recognition applications like hand-written math equations and East-Asian character recognition is pursued jointly with peer groups.