3 accepted papers
Several studies have shown promising results in adapting DNN-based acoustic models as a mechanism to transfer characteristics from pre-trained models. One such example is speaker adaptation using a small amount of data, where fine-tuning has helped train models that extrapolate well to diverse lingu…
A speaker embeddings framework achieves state-of-the-art speaker recognition performance by modeling speaker discriminant information directly using deep neural networks (DNNs). After the introduction of neural network based speaker embeddings, researchers have explored the requirements for training…
Automatic speech recognition from distant microphones is a difficult task because recordings are affected by reverberation and background noise. First, the application of the deep neural network (DNN)/hidden Markov model (HMM) hybrid acoustic models for distant speech recognition task using AMI meet…