39 citations · 51 across the 6 of their papers we have counts for
7 papers
Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?
Eklavya Sarkar, Mathew Magimai. -Doss
Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an…
Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering
Eklavya Sarkar, RaviShankar Prasad, Mathew Magimai. -Doss
Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which conta…
Comparing supervised and self-supervised embedding for ExVo Multi-Task learning track
Tilak Purohit, Imen Ben Mahmoud, Bogdan Vlasenko +1
The ICML Expressive Vocalizations (ExVo) Multi-task challenge 2022, focuses on understanding the emotional facets of the non-linguistic vocalizations (vocal bursts (VB)). The objec…
An Objective Evaluation Framework for Pathological Speech Synthesis
Bence Mark Halpern, Julian Fritsch, Enno Hermann +3
The development of pathological speech systems is currently hindered by the lack of a standardised objective evaluation framework. In this work, (1) we utilise existing detection a…
Learning linearly separable features for speech recognition using convolutional neural networks
Dimitri Palaz, Mathew Magimai Doss, Ronan Collobert
Automatic speech recognition systems usually rely on spectral-based features, such as MFCC of PLP. These features are extracted based on prior knowledge such as, speech perception…
End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks
Dimitri Palaz, Ronan Collobert, Mathew Magimai. -Doss
Most phoneme recognition state-of-the-art systems rely on a classical neural network classifiers, fed with highly tuned features, such as MFCC or PLP features. Recent advances in `…
Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks
Dimitri Palaz, Ronan Collobert, Mathew Magimai. -Doss
In hybrid hidden Markov model/artificial neural networks (HMM/ANN) automatic speech recognition (ASR) system, the phoneme class conditional probabilities are estimated by first ext…