5 citations · 21 across the 12 of their papers we have counts for
14 papers
Test-Time Compute Scaling for ASR with Depth-Conditioned Looped Transformers
Yacouba Kaloga, Shashi Kumar, Shakeel A. Sheikh +3
End-to-end ASR systems typically use fixed-depth acoustic encoders at inference, making it difficult to trade additional test-time computation for improved recognition without trai…
Virtual Speech Therapist: A Clinician-in-the-Loop AI Agent for Speech Therapy Planning
Shakeel Sheikh, Patrick Marmaroli, MD Sahidullah +4
This paper presents a proof of concept of the Virtual Speech Therapist (VST), an intelligent multi-agent based system designed to support stuttering assessment and individualized t…
Overview of Automatic Speech Analysis and Technologies for Neurodegenerative Disorders: Diagnosis and Assistive Applications
Shakeel A. Sheikh, Md. Sahidullah, Ina Kodrasi
Advancements in spoken language technologies for neurodegenerative speech disorders are crucial for meeting both clinical and technological needs. This overview paper is vital for…
Graph Neural Networks for Parkinsons Disease Detection
Shakeel A. Sheikh, Yacouba Kaloga, Md Sahidullah +1
Despite the promising performance of state of the art approaches for Parkinsons Disease (PD) detection, these approaches often analyze individual speech segments in isolation, whic…
Multiview Canonical Correlation Analysis for Automatic Pathological Speech Detection
Yacouba Kaloga, Shakeel A. Sheikh, Ina Kodrasi
Recently proposed automatic pathological speech detection approaches rely on spectrogram input representations or wav2vec2 embeddings. These representations may contain pathology i…
Impact of Speech Mode in Automatic Pathological Speech Detection
Shakeel A. Sheikh, Ina Kodrasi
Automatic pathological speech detection approaches yield promising results in identifying various pathologies. These approaches are typically designed and evaluated for phoneticall…
Selfsupervised learning for pathological speech detection
Shakeel Ahmad Sheikh
Speech production is a complex phenomenon, wherein the brain orchestrates a sequence of processes involving thought processing, motor planning, and the execution of articulatory mo…
Stuttering Detection Using Speaker Representations and Self-supervised Contextual Embeddings
Shakeel A. Sheikh, Md Sahidullah, Fabrice Hirsch +1
The adoption of advanced deep learning architectures in stuttering detection (SD) tasks is challenging due to the limited size of the available datasets. To this end, this work int…
Advancing Stuttering Detection via Data Augmentation, Class-Balanced Loss and Multi-Contextual Deep Learning
Shakeel A. Sheikh, Md Sahidullah, Fabrice Hirsch +1
Stuttering is a neuro-developmental speech impairment characterized by uncontrolled utterances (interjections) and core behaviors (blocks, repetitions, and prolongations), and is c…
End-to-End and Self-Supervised Learning for ComParE 2022 Stuttering Sub-Challenge
Shakeel Ahmad Sheikh, Md Sahidullah, Fabrice Hirsch +1
In this paper, we present end-to-end and speech embedding based systems trained in a self-supervised fashion to participate in the ACM Multimedia 2022 ComParE Challenge, specifical…
Robust Stuttering Detection via Multi-task and Adversarial Learning
Shakeel Ahmad Sheikh, Md Sahidullah, Fabrice Hirsch +1
By automatic detection and identification of stuttering, speech pathologists can track the progression of disfluencies of persons who stutter (PWS). In this paper, we investigate t…
Introducing ECAPA-TDNN and Wav2Vec2.0 Embeddings to Stuttering Detection
Shakeel Ahmad Sheikh, Md Sahidullah, Fabrice Hirsch +1
The adoption of advanced deep learning (DL) architecture in stuttering detection (SD) tasks is challenging due to the limited size of the available datasets. To this end, this work…
Machine Learning for Stuttering Identification: Review, Challenges and Future Directions
Shakeel Ahmad Sheikh, Md Sahidullah, Fabrice Hirsch +1
Stuttering is a speech disorder during which the flow of speech is interrupted by involuntary pauses and repetition of sounds. Stuttering identification is an interesting interdisc…
StutterNet: Stuttering Detection Using Time Delay Neural Network
Shakeel A. Sheikh, Md Sahidullah, Fabrice Hirsch +1
This paper introduces StutterNet, a novel deep learning based stuttering detection capable of detecting and identifying various types of disfluencies. Most of the existing work in…