19 citations · 23 across the 6 of their papers we have counts for
7 papers · 1 filter
Building English ASR model with regional language support
Purvi Agrawal, Vikas Joshi, Bharati Patidar +2
In this paper, we present a novel approach to developing an English Automatic Speech Recognition (ASR) system that can effectively handle Hindi queries, without compromising its pe…
Streaming Bilingual End-to-End ASR model using Attention over Multiple Softmax
Aditya Patil, Vikas Joshi, Purvi Agrawal +1
Even with several advancements in multilingual modeling, it is challenging to recognize multiple languages using a single neural model, without knowing the input language and most…
A Multi-Head Relevance Weighting Framework For Learning Raw Waveform Audio Representations
Debottam Dutta, Purvi Agrawal, Sriram Ganapathy
In this work, we propose a multi-head relevance weighting framework to learn audio representations from raw waveforms. The audio waveform, split into windows of short duration, are…
Representation Learning For Speech Recognition Using Feedback Based Relevance Weighting
Purvi Agrawal, Sriram Ganapathy
In this work, we propose an acoustic embedding based approach for representation learning in speech recognition. The proposed approach involves two stages comprising of acoustic fi…
Interpretable Representation Learning for Speech and Audio Signals Based on Relevance Weighting
Purvi Agrawal, Sriram Ganapathy
The learning of interpretable representations from raw data presents significant challenges for time series data like speech. In this work, we propose a relevance weighting scheme…
Robust Raw Waveform Speech Recognition Using Relevance Weighted Representations
Purvi Agrawal, Sriram Ganapathy
Speech recognition in noisy and channel distorted scenarios is often challenging as the current acoustic modeling schemes are not adaptive to the changes in the signal distribution…
Interpretable Filter Learning Using Soft Self-attention For Raw Waveform Speech Recognition
Purvi Agrawal, Sriram Ganapathy
Speech recognition from raw waveform involves learning the spectral decomposition of the signal in the first layer of the neural acoustic model using a convolution layer. In this w…