Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …

Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …

The objective of this paper is' open-set'speaker recognition of unseen speakers, where ideal
embeddings should be able to condense information into a compact utterance-level …

While speaker adaptation for end-to-end speech synthesis using speaker embeddings can
produce good speaker similarity for speakers seen during training, there remains a gap for …

Voice is a behavioral biometric that conveys information related to a person's traits, such as
the speaker's ethnicity, age, gender, and feeling. Speaker recognition deals with recognizing …

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 …

In this work, we explore the dependencies between speaker recognition and emotion
recognition. We first show that knowledge learned for speaker recognition can be reused for …

The speech signal contains a vast spectrum of information about the speaker such as
speakers' gender, age, accent, or health state. In this paper, we explored different …

Time delay neural network (TDNN) has been widely used in speaker verification tasks.
Recently, two TDNN-based models, including extended TDNN (E-TDNN) and factorized …

In this paper, we propose VoiceID loss, a novel loss function for training a speech
enhancement model to improve the robustness of speaker verification. In contrast to the …