284 citations · 354 across the 12 of their papers we have counts for
12 papers
MemToolAgent: Leveraging Memory for Tool Using Agents Based on Environment and User Feedback
Suleyman Armagan Er, Danilo Ribeiro, Yogesh Virkar +5
Modern large language model (LLM) agents can use external tools to help users solve complex tasks. However, for problems that require learning from long-term historical events or f…
Speaker Diarization of Scripted Audiovisual Content
Yogesh Virkar, Brian Thompson, Rohit Paturi +2
The media localization industry usually requires a verbatim script of the final film or TV production in order to create subtitles or dubbing scripts in a foreign language. In part…
Improving Isochronous Machine Translation with Target Factors and Auxiliary Counters
Proyag Pal, Brian Thompson, Yogesh Virkar +3
To translate speech for automatic dubbing, machine translation needs to be isochronous, i.e. translated speech needs to be aligned with the source in terms of speech durations. We…
Jointly Optimizing Translations and Speech Timing to Improve Isochrony in Automatic Dubbing
Alexandra Chronopoulou, Brian Thompson, Prashant Mathur +3
Automatic dubbing (AD) is the task of translating the original speech in a video into target language speech. The new target language speech should satisfy isochrony; that is, the…
Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing
William Brannon, Yogesh Virkar, Brian Thompson
We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produc…
Prosodic Alignment for off-screen automatic dubbing
Yogesh Virkar, Marcello Federico, Robert Enyedi +1
The goal of automatic dubbing is to perform speech-to-speech translation while achieving audiovisual coherence. This entails isochrony, i.e., translating the original speech by als…
Isometric MT: Neural Machine Translation for Automatic Dubbing
Surafel M. Lakew, Yogesh Virkar, Prashant Mathur +1
Automatic dubbing (AD) is among the machine translation (MT) use cases where translations should match a given length to allow for synchronicity between source and target speech. F…
Isochrony-Aware Neural Machine Translation for Automatic Dubbing
Derek Tam, Surafel M. Lakew, Yogesh Virkar +2
We introduce the task of isochrony-aware machine translation which aims at generating translations suitable for dubbing. Dubbing of a spoken sentence requires transferring the cont…
Dynamic regulation of resource transport induces criticality in interdependent networks of excitable units
Yogesh S. Virkar, Juan G. Restrepo, Woodrow L. Shew +1
Various functions of a network of excitable units can be enhanced if the network is in the `critical regime', where excitations are, on average, neither damped nor amplified. An im…
Metabolite transport through glial networks stabilizes the dynamics of learning
Yogesh S. Virkar, Woodrow L. Shew, Juan G. Restrepo +1
Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality…
The Hamiltonian Mean Field model: effect of network structure on synchronization dynamics
Yogesh S. Virkar, Juan G. Restrepo, James D. Meiss
The Hamiltonian Mean Field (HMF) model of coupled inertial, Hamiltonian rotors is a prototype for conservative dynamics in systems with long-range interactions. We consider the cas…
Power-law distributions in binned empirical data
Yogesh Virkar, Aaron Clauset
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities and size of international wars, are believed to follow power-law distributions. Th…