by Greg Sell, Senior Research Scientist A team of Johns Hopkins researchers from the HLTCOE and CLSP participated in the recent DIHARD challenge. In the evaluation, teams were given audio recordings of speech from a diverse set of conditions with an unknown number of speakers, with the goal of correctly marking the times that each […]
Cross-lingual information extraction is the task of distilling facts from foreign language (e.g. Chinese text) into representations in another language that is preferred by the user (e.g. English tuples). Conventional pipeline solutions decompose the task as machine translation followed by information extraction (or vice versa). We propose a joint solution with a neural sequence model, […]
by Kevin Duh, Senior Research Scientist The HLTCOE has acquired a NVIDIA DGX-1 Deep Learning System to support its numerous deep learning research efforts. With eight Tesla P100 GPUs, this brand new system delivers 170 teraflops of computing power (equivalent to 250 x86 servers) and has been described as an “AI Supercomputer in a […]
The Cambridge University effect from the psycholinguistics literature has demonstrated a robust word processing mechanism in humans, where jumbled words (e.g. Cmabrigde /Cambridge) are recognized with little cost. Inspired by the findings from the Cambrigde University effect, we propose a word recognition model based on a semi-character level recursive neural network (scRNN). In our experiments, […]
Social media users who share conspiracy theories and pseudoscientific claims about the Zika virus may undermine upcoming efforts to keep the disease from spreading, according to a study published online today by the journal Vaccine. The researchers behind the study—from Johns Hopkins University, George Washington University, and the University of Georgia—say the misinformation they detected […]
