LTI Associate Professor Bhiksha Raj has been named to the 2017 class of IEEE fellows for his "contributions to speech recognition," according to IEEE.
Established more than a hundred years ago, the IEEE fellow grade is a distinction reserved for select IEEE members whose extraordinary accomplishments in any of the organization's fields of interest are deemed fitting of... Read More
For the second consecutive year, Carnegie Mellon came out on top in the LiveQA evaluation – an exercise that requires question-answering (QA) software to respond to real-time questions received by the Yahoo! Answers website – at the Text Retrieval Conference (TREC 2016).
A team of students from the Language Technologies Institute recently earned top honors for their performance in the BioASQ 2016 Biomedical Semantic Question Answering challenge.
Held annually, BioASQ pushes for a solution to the information access problem biomedical experts face by posing challenges on both biomedical semantic indexing and question answering. The CMU team, comprising Zi Yang, a student in the LTI's Ph.D. program; Yue Zhou, a student in the... Read More
We're currently seeking applicants for both tenure-track and teaching-track faculty positions. Please see the links below for more information on available positions, as well as instructions for applying:Read More
Massive Open Online Courses (MOOCs) have great potential to change where and how people learn. But MOOCs have a typical completion rate in the single digits. One reason for such dismal results? Possibly the lack of social interaction experienced in online learning.
Despite rapid improvements in machine learning technologies, real-time machine translation algorithms still make mistakes that humans would find unthinkable. A team of researchers from the Language Technologies Institute, New York University, and The University of Hong Kong recently published a paper demonstrating that, for the first time, certain algorithms can perform simultaneous speech translation much better than previous algorithms.
The paper, published Oct. 3, was featured in a recent article on... Read More
Kill or be killed is the essence of the classic video game Doom, and an artificial intelligence agent developed by two Language Technologies Institute students has proven to be the game's ultimate survivor — outplaying both the game's built-in AI agents and human players.
The students, Devendra Chaplot and Guillaume Lample, used deep-learning techniques to train the AI agent to negotiate the game's 3-D environment, still challenging after more than two decades because players must act based only on the portion of the game visible on the screen.
Their work follows the... Read More
How much of an interaction between two people is strictly verbal? Often, a person might say one thing, while an in-depth analysis of their facial expressions reveals something totally different. To help connect the disconnect between verbal communication and expression, Language Technologies Institute Postdoctoral Researcher Tadas Baltrusaitis has created facial-recognition software known as OpenFace.
Baltrusaitis spoke to... Read More
The voice is a significant component of human interaction that allows us to characterize each other, and voice-activated and identification technologies are at the forefront of research to personalize day-to-day interactions with technology. Carnegie Mellon University's Rita Singh, a senior systems scientist in the Language Technologies Institute, recently spoke to CSO Online... Read More
In the spring of 2013, Language Technologies Institute Ph.D. student Leonid Boytsov and Bilegsaikhan (Bileg) Naidan, a Ph.D. student at the Norwegian University of Science and Technology, had a problem. They needed to evaluate a novel nearest-neighbor search method for non-metric spaces, but no adequate software suite was available.
So they built one.