Search Results for author:
Found 9 papers, 0 papers with code
Joint Communication and Sensing for 6G -- A Cross-Layer Perspective
As 6G emerges, cellular systems are envisioned to integrate sensing with communication capabilities, leading to multi-faceted communication and sensing (JCAS).
P-Mamba: Marrying Perona Malik Diffusion with Mamba for Efficient Pediatric Echocardiographic Left Ventricular Segmentation
In pediatric cardiology, the accurate and immediate assessment of cardiac function through echocardiography is important since it can determine whether urgent intervention is required in many emergencies.
Exploring linguistic feature and model combination for speech recognition based automatic AD detection
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and delay progression.
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care to delay further progression.
On-the-Fly Feature Based Rapid Speaker Adaptation for Dysarthric and Elderly Speech Recognition
Accurate recognition of dysarthric and elderly speech remain challenging tasks to date.
Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition
Motivated by the spectro-temporal level differences between dysarthric, elderly and normal speech that systematically manifest in articulatory imprecision, decreased volume and clarity, slower speaking rates and increased dysfluencies, novel spectrotemporal subspace basis deep embedding features derived using SVD speech spectrum decomposition are proposed in this paper to facilitate auxiliary feature based speaker adaptation of state-of-the-art hybrid DNN/TDNN and end-to-end Conformer speech recognition systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Spectro-Temporal Deep Features for Disordered Speech Assessment and Recognition
Automatic recognition of disordered speech remains a highly challenging task to date.
Bayesian Transformer Language Models for Speech Recognition
Performance improvements were also obtained on a cross domain LM adaptation task requiring porting a Transformer LM trained on the Switchboard and Fisher data to a low-resource DementiaBank elderly speech corpus.
Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition
On a third cross domain adaptation task requiring rapidly porting a 1000 hour LibriSpeech data trained system to a small DementiaBank elderly speech corpus, the proposed Bayesian TDNN LF-MMI systems outperformed the baseline system using direct weight fine-tuning by up to 2. 5\% absolute WER reduction.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
