SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to facilitate the
research and development of neural speech processing technologies by being simple …

The recently proposed VBx diarization method uses a Bayesian hidden Markov model to
find speaker clusters in a sequence of x-vectors. In this work we perform an extensive …

Speaker recognition is related to human biometrics dealing with the identification of
speakers from their speech. Speaker recognition is an active research area and being …

In this paper, we propose TitaNet, a novel neural network architecture for extracting speaker
representations. We employ 1D depth-wise separable convolutions with Squeeze-and …

Learning robust speaker embeddings is a crucial step in speaker diarization. Deep neural
networks can accurately capture speaker discriminative characteristics and popular deep …

为了追求精度, 深度学习模型框架的结构越来越复杂, 网络越来越深. 参数量的增加意味着训练
模型需要更多的数据. 然而人工标注数据的成本是高昂的, 且受客观原因所限 …

Automatic speaker verification (ASV) exhibits unsatisfactory performance under domain
mismatch conditions owing to intrinsic and extrinsic factors, such as variations in speaking …

Significant progress has recently been made in speaker diarisation after the introduction of d-
vectors as speaker embeddings extracted from neural network (NN) speaker classifiers for …

Speaker diarization is the partitioning of an audio source stream into homogeneous
segments according to the speaker's identity. It can improve the readability of an automatic …

Speaker recognition deals with recognizing speakers by their speech. Most speaker
recognition systems are built upon two stages, the first stage extracts low dimensional …