2 citations · 3 across the 12 of their papers we have counts for
10 papers · 1 filter
Leveraging AM and FM Rhythm Spectrograms for Dementia Classification and Assessment
Parismita Gogoi, Vishwanath Pratap Singh, Seema Khadirnaikar +6
This study explores the potential of Rhythm Formant Analysis (RFA) to capture long-term temporal modulations in dementia speech. Specifically, we introduce RFA-derived rhythm spect…
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence
Edem Ahadzi, Vishwanath Pratap Singh, Tomi Kinnunen +1
In this work, we present the first study addressing automatic speech recognition (ASR) for children in an online learning setting. This is particularly important for both child-cen…
Causal Analysis of ASR Errors for Children: Quantifying the Impact of Physiological, Cognitive, and Extrinsic Factors
Vishwanath Pratap Singh, Md. Sahidullah, Tomi Kinnunen
The increasing use of children's automatic speech recognition (ASR) systems has spurred research efforts to improve the accuracy of models designed for children's speech in recent…
ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech
Xin Wang, Héctor Delgado, Hemlata Tak +26
ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks as well as the design of detection solutions. We introduce…
ROAR: Reinforcing Original to Augmented Data Ratio Dynamics for Wav2Vec2.0 Based ASR
Vishwanath Pratap Singh, Federico Malato, Ville Hautamaki +2
While automatic speech recognition (ASR) greatly benefits from data augmentation, the augmentation recipes themselves tend to be heuristic. In this paper, we address one of the heu…
ChildAugment: Data Augmentation Methods for Zero-Resource Children's Speaker Verification
Vishwanath Pratap Singh, Md Sahidullah, Tomi Kinnunen
The accuracy of modern automatic speaker verification (ASV) systems, when trained exclusively on adult data, drops substantially when applied to children's speech. The scarcity of…
Speaker Verification Across Ages: Investigating Deep Speaker Embedding Sensitivity to Age Mismatch in Enrollment and Test Speech
Vishwanath Pratap Singh, Md Sahidullah, Tomi Kinnunen
In this paper, we study the impact of the ageing on modern deep speaker embedding based automatic speaker verification (ASV) systems. We have selected two different datasets to exa…
Spectral Modification Based Data Augmentation For Improving End-to-End ASR For Children's Speech
Vishwanath Pratap Singh, Hardik Sailor, Supratik Bhattacharya +1
Training a robust Automatic Speech Recognition (ASR) system for children's speech recognition is a challenging task due to inherent differences in acoustic attributes of adult and…
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…