1 citations · 4 across the 4 of their papers we have counts for
4 papers
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…
Artimate: an articulatory animation framework for audiovisual speech synthesis
Ingmar Steiner, Slim Ouni
We present a modular framework for articulatory animation synthesis using speech motion capture data obtained with electromagnetic articulography (EMA). Adapting a skeletal animati…