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This paper introduces StutterNet, a novel deep learning based stutteringdetection capable of detecting and identifying various types of disfluencies.Most of the existing work in this domain uses automatic speech recognition(ASR) combined with language models for stuttering detection. Compared to theexisting work, which depends on the ASR module, our method relies solely on theacoustic signal. We use a time-delay neural network (TDNN) suitable forcapturing contextual aspects of the disfluent utterances. We evaluate oursystem on the UCLASS stuttering dataset consisting of more than 100 speakers.Our method achieves promising results and outperforms the state-of-the-artresidual neural network based method. The number of trainable parameters of theproposed method is also substantially less due to the parameter sharing schemeof TDNN.

StutterNet: Stuttering Detection Using Time Delay Neural Network