4 citations · 5 across the 6 of their papers we have counts for
9 papers
I see what you hear: a vision-inspired method to localize words
Mohammad Samragh, Arnav Kundu, Ting-Yao Hu +5
This paper explores the possibility of using visual object detection techniques for word localization in speech data. Object detection has been thoroughly studied in the contempora…
Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition
Ting-Yao Hu, Mohammadreza Armandpour, Ashish Shrivastava +3
With recent advances in speech synthesis, synthetic data is becoming a viable alternative to real data for training speech recognition models. However, machine learning with synthe…
SLAP: A Split Latency Adaptive VLIW pipeline architecture which enables on-the-fly variable SIMD vector-length
Ashish Shrivastava, Alan Gatherer, Tong Sun +2
Over the last decade the relative latency of access to shared memory by multicore increased as wire resistance dominated latency and low wire density layout pushed multiport memori…
Towards a Domain Specific Solution for a New Generation of Wireless Modems
Alan Gatherer, Ashish Shrivastava, Hao Luan +3
Wireless cellular System on Chip (SoC) are experiencing unprecedented demands on data rate, latency use case variety. 5G wireless technologies require a massive number of antennas…
Saying No is An Art: Contextualized Fallback Responses for Unanswerable Dialogue Queries
Ashish Shrivastava, Kaustubh Dhole, Abhinav Bhatt +1
Despite end-to-end neural systems making significant progress in the last decade for task-oriented as well as chit-chat based dialogue systems, most dialogue systems rely on hybrid…
SapAugment: Learning A Sample Adaptive Policy for Data Augmentation
Ting-Yao Hu, Ashish Shrivastava, Jen-Hao Rick Chang +5
Data augmentation methods usually apply the same augmentation (or a mix of them) to all the training samples. For example, to perturb data with noise, the noise is sampled from a N…