by Susie Cribbs | Friday, October 14, 2016

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.

Carolyn Rosé, an associate professor in the LTI, hopes to change that with her latest research on MOOCs and online learning. A recent article by edSurge... Read More

by Susie Cribbs | Wednesday, October 12, 2016

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

LTI Students Use Deep Learning To Master Videogame's 3-D World
by Byron Spice | Tuesday, September 27, 2016

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

by Aisha Rashid | Friday, September 23, 2016

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

Rita Singh Talks Cutting-Edge Vocal Recognition Technology
by Aisha Rashid | Tuesday, September 13, 2016

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

by Susie Cribbs | Monday, August 15, 2016

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.

That software, Non-Metric Space Library (NMSLIB), is available to the public and gaining traction... Read More

LTI's Alan Black Part of Team Making Software Available for Free
by Byron Spice | Monday, August 8, 2016

Millions of visually impaired people in India may benefit from free, open-source software for Android devices that converts electronic text written in Indian languages into messages they can hear.

The text-to-speech (TTS) software, developed by Carnegie Mellon University in collaboration with the Hear2Read project, can now be downloaded free of charge from Google Play. Tamil is the first language offered, with subsequent releases of seven... Read More

by Susie Cribbs | Wednesday, August 3, 2016

A paper by a team of School of Computer Science researchers has been named one of nine outstanding long papers at the Association for Computational Linguistics annual meeting (ACL 2016). The conference, to be held Aug. 7–12 in Berlin, offers tutorials, workshops and presentations on the latest research in a broad spectrum of diverse research areas concerned with computational approaches to natural language.

The paper, "Harnessing Deep Neural... Read More

by Susie Cribbs | Tuesday, July 26, 2016

Most social media users know the story: You're reading your newsfeed and open a new tab on your browser to do some shopping. The next time you log in to whatever social media platform you'd used, the advertisements miraculously relate directly to what you'd been shopping for. Coincidence? No way. Machine learning techniques are working way below the surface to determine what you're looking at and what deals apply to you.

Imagine if you could harness that technology so you'd receive a message when you were near a store offering just what you were looking for — from the perfect... Read More

by Susie Cribbs | Thursday, July 21, 2016

In 2000, Carnegie Mellon University's School of Computer Science Sphinx group released a collection of open-source speech recognition development libraries and tools that, over time, came to be known as CMUSphinx. Late last month, the group celebrated 1.5 million downloads of this toolkit, which is used for speech recognition research and building speech products.

Begun as a DARPA-funded project, Sphinx is committed to widely releasing its... Read More

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