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Stuttering Detection Using Speaker Representations and Self-supervised Contextual Embeddings
The adoption of advanced deep learning architectures in stuttering detection (SD) tasks is challenging due to the limited size of the available datasets.
Advancing Stuttering Detection via Data Augmentation, Class-Balanced Loss and Multi-Contextual Deep Learning
In addition, we propose a multi-contextual (MC) StutterNet, which exploits different contexts of the stuttered speech, resulting in an overall improvement of 4. 48% in F 1 over the single context based MB StutterNet.
StutterNet: Stuttering Detection Using Time Delay Neural Network
Compared to the existing work, which depends on the ASR module, our method relies solely on the acoustic signal.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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