1.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Research!America (United States)US21 papers
- Samsung (South Korea)KR17 papers
- Korea Advanced Institute of Science and TechnologyKR9 papers
- Korea Institute of Science and TechnologyKR7 papers
- University of CambridgeGB5 papers
- University of Southern CaliforniaUS5 papers
- Imperial College LondonGB4 papers
- Purdue University West LafayetteUS4 papers
- Samsung Electronics (South Korea)KR4 papers
- Samsung (India)IN4 papers
- Stanford UniversityUS4 papers
- Texas A&M UniversityUS4 papers
5 papers · 2 filters
A Mixture of Expert Based Deep Neural Network for Improved ASR
Vishwanath Pratap Singh, Shakti P. Rath, Abhishek Pandey
This paper presents a novel deep learning architecture for acoustic model in the context of Automatic Speech Recognition (ASR), termed as MixNet. Besides the conventional layers, s…
A higher order Minkowski loss for improved prediction ability of acoustic model in ASR
Vishwanath Pratap Singh, Shakti P. Rath, Abhishek Pandey
Conventional automatic speech recognition (ASR) system uses second-order minkowski loss during inference time which is suboptimal as it incorporates only first order statistics in…
North America Bixby Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2021
Myungjong Kim, Taeyeon Ki, Aviral Anshu +1
This paper describes the submission to the speaker diarization track of VoxCeleb Speaker Recognition Challenge 2021 done by North America Bixby Lab of Samsung Research America. Our…
SRIB Submission to Interspeech 2021 DiCOVA Challenge
Vishwanath Pratap Singh, Shashi Kumar, Ravi Shekhar Jha +1
The COVID-19 pandemic has resulted in more than 125 million infections and more than 2.7 million casualties. In this paper, we attempt to classify covid vs non-covid cough sounds u…
X-Vectors with Multi-Scale Aggregation for Speaker Diarization
Myungjong Kim, Vijendra Raj Apsingekar, Divya Neelagiri
Speaker diarization is the process of labeling different speakers in a speech signal. Deep speaker embeddings are generally extracted from short speech segments and clustered to de…