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20162026
most citedGeneralizing Across Domains via Cross-Gradient Training

337 citations · 470 across the 50 of their papers we have counts for

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Showing 2021Show all

13 papers · 1 filter

cs.SD2021

SpliceOut: A Simple and Efficient Audio Augmentation Method

Arjit Jain, Pranay Reddy Samala, Deepak Mittal +2

Time masking has become a de facto augmentation technique for speech and audio tasks, including automatic speech recognition (ASR) and audio classification, most notably as a part…

eess.AS2021★ 4 cited

DITTO: Data-efficient and Fair Targeted Subset Selection for ASR Accent Adaptation

Suraj Kothawade, Anmol Mekala, Chandra Sekhara D +4

State-of-the-art Automatic Speech Recognition (ASR) systems are known to exhibit disparate performance on varying speech accents. To improve performance on a specific target accent…

eess.AS2021★ 1 cited

Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights

Devaraja Adiga, Rishabh Kumar, Amrith Krishna +3

Automatic speech recognition (ASR) in Sanskrit is interesting, owing to the various linguistic peculiarities present in the language. The Sanskrit language is lexically productive,…

cs.CL2021

The Effectiveness of Intermediate-Task Training for Code-Switched Natural Language Understanding

Archiki Prasad, Mohammad Ali Rehan, Shreya Pathak +1

While recent benchmarks have spurred a lot of new work on improving the generalization of pretrained multilingual language models on multilingual tasks, techniques to improve code-…

cs.CL2021

From Machine Translation to Code-Switching: Generating High-Quality Code-Switched Text

Ishan Tarunesh, Syamantak Kumar, Preethi Jyothi

Generating code-switched text is a problem of growing interest, especially given the scarcity of corpora containing large volumes of real code-switched text. In this work, we adapt…

cs.SD2021

Cross-Modal learning for Audio-Visual Video Parsing

Jatin Lamba, Abhishek, Jayaprakash Akula +3

In this paper, we present a novel approach to the audio-visual video parsing (AVVP) task that demarcates events from a video separately for audio and visual modalities. The propose…