5 citations · 21 across the 12 of their papers we have counts for
3 papers · 1 filter
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…