Many speaker recognition challenges have been held to assess the speaker verification
system in the wild and probe the performance limit. Voxceleb Speaker Recognition …

This paper proposes a method for extracting speaker embedding for each speaker from a
variable-length recording containing multiple speakers. Speaker embeddings are crucial not …

In this paper, we propose a new hybrid system for extracting a speaker embedding vector.
More specifically, the proposed system employs a multi-level global-local statistics pooling …

Extraction of a speaker embedding vector plays an important role in deep learning-based
speaker verification. In this contribution, to extract speaker discriminant utterance level …

Text-dependent speaker verification systems trained on large amount of labelled data
exhibit remarkable performance. However, collecting the speech from a lot of speakers with …

In neural speaker verification, statistics pooling plays a key role in the learning and
extraction of a speaker embedding vector. In this contribution, we perform an investigative …

Data augmentation is vital to the generalization ability and robustness of deep neural
networks (DNNs) models. Existing augmentation methods for speaker verification …

Data augmentation is commonly used to help build a robust speaker verification system,
especially in limited-resource case. However, conventional data augmentation methods …

In this contribution, we propose a multi-stream hybrid neural network for extracting speaker
discriminant utterance-level embedding vectors. In this approach, an input acoustic feature …

In this paper, we provide description of our experimented systems on the CNCeleb dataset.
The CNCeleb dataset provides a difficult set of trial that were collected from multiple genres …