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Aravind Illa

8 accepted papers

2022

The impact of cross language on acoustic-to-articulatory inversion and its influence on articulatory speech synthesis

ICASSP 2022accepted

Estimating articulatory representations (ARs) from acoustic features is known as acoustic-to-articulatory inversion (AAI). Various factors of input acoustic features impact the performance of AAI. In this work, we investigate the effect of unseen language on the AAI performance in both seen and unse…

Cited by 0SourceScholar
2021

Acoustic-to-Articulatory Inversion for Dysarthric Speech by Using Cross-Corpus Acoustic-Articulatory Data

ICASSP 2021accepted

In this work, we focus on estimating articulatory movements from acoustic features, known as acoustic-to-articulatory inversion (AAI), for dysarthric patients with amyotrophic lateral sclerosis (ALS). Unlike healthy subjects, there are two potential challenges involved in AAI on dysarthric speech. D…

Cited by 0SourceScholar
2020

A Comparative Study of Estimating Articulatory Movements from Phoneme Sequences and Acoustic Features

ICASSP 2020accepted

Unlike phoneme sequences, movements of speech articulators (lips, tongue, jaw, velum) and the resultant acoustic signal are known to encode not only the linguistic message but also carry para-linguistic information. While several works exist for estimating articulatory movement from acoustic signals…

Cited by 0SourceScholar
2020

Voice based classification of patients with Amyotrophic Lateral Sclerosis, Parkinson's Disease and Healthy Controls with CNN-LSTM using transfer learning

ICASSP 2020accepted

In this paper, we consider 2-class and 3-class classification problems for classifying patients with Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD), and Healthy Controls (HC) using a CNNLSTM network. Classification performance is examined for three different tasks, namely, Spontaneous…

Cited by 30SourceScholar
2019

A Study on Robustness of Articulatory Features for Automatic Speech Recognition of Neutral and Whispered Speech

ICASSP 2019accepted

Traditionally, automatic speech recognition (ASR) systems are trained on acoustic representations of neutral speech. As a result, their performance degrades when tested with whispered speech. In this work, we explore the robustness of articulatory features in ASR of neutral and whispered speech. We…

Cited by 0SourceScholar
2019

Representation Learning Using Convolution Neural Network for Acoustic-to-articulatory Inversion

ICASSP 2019accepted

Recent techniques employ end-to-end systems to learn relevant features for several speech related applications, including speech recognition, and speaker verification. In this work, we focus on the task of acoustic-to-articulatory inversion (AAI) for which we propose an end-to-end system that compri…

Cited by 0SourceScholar
2018

Comparison of Speech Tasks for Automatic Classification of Patients with Amyotrophic Lateral Sclerosis and Healthy Subjects

ICASSP 2018accepted

In this work, we consider the task of acoustic and articulatory feature based automatic classification of Amyotrophic Lateral Sclerosis (ALS) patients and healthy subjects using speech tasks. In particular, we compare the roles of different types of speech tasks, namely rehearsed speech, spontaneous…

Cited by 0SourceScholar
2017

A comparative study of acoustic-to-articulatory inversion for neutral and whispered speech

ICASSP 2017accepted

Whispered speech is known to have different characteristics in acoustics and articulation compared to neutral speech. In this study, we compare the accuracy with which the articulation can be recovered from the acoustics of both types of speech, individually. Acoustic-to-articulatory inversion (AAI)…

Cited by 0SourceScholar