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.
Video
Hope Speech and Help Speech: Surfacing Positivity Amidst Hate
Tackling online attacks targeting certain individuals, groups of people, or communities is a major modern-day web challenge. Research efforts in hate speech detection thus far have largely focused on identifying and subsequently filtering out negative…
Tool
GLUECoS
This is the repo for the ACL 2020 paper GLUECoS: An Evaluation Benchmark for Code-Switched NLP GLUECoS is a benchmark comprising of multiple code-mixed tasks across 2 language pairs (En-Es and En-Hi)
Project
PROSE Framework
Microsoft PROSE SDK is a framework of technologies for programming by examples: automatic generation of programs from input-output examples.
Project
Project EPOCh: Extending Patient Outreach with Chat
Patient-centred care and good communication between patients and healthcare providers has been shown to improve medical adherence. However, it is costly and difficult to provide, especially in Global Health settings where patient volumes are high…
Group
Azure Cognitive Services Research
The mission of the Cognitive Services Research group (CSR) is to make fundamental contributions to advancing the state of the art of the most challenging problems in speech, language, and vision both within Microsoft and…
Tool
MIcrosoft News Dataset (MIND)
MIcrosoft News Dataset (MIND) is a large-scale dataset for news recommendation research. It was collected from anonymized behavior logs of Microsoft News website. The mission of MIND is to serve as a benchmark dataset for…
Project
Trustworthy AI
In recent times, the explosion of information from a variety of sources and cutting edge techniques such as Deepfake have made it increasingly important to check the credibility and reliability of the data. Large volumes…
Project
Learning with Weak Supervision
The need for labeled data is one of the largest bottlenecks in training supervised learning models like deep neural networks. This is especially the case for many real-world tasks where large scale annotated examples are…