The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

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

The objective of this work is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …

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 …

The objective of this paper is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual speaker …

In this paper, we present Multi-scale Feature Aggregation Conformer (MFA-Conformer), an
easy-to-implement, simple but effective backbone for automatic speaker verification based …

Most existing datasets for speaker identification contain samples obtained under quite
constrained conditions, and are usually hand-annotated, hence limited in size. The goal of …

The objective of this paper is speaker recognitionin the wild'-where utterances may be of
variable length and also contain irrelevant signals. Crucial elements in the design of deep …

For speaker recognition, it is difficult to extract an accurate speaker representation from
speech because of its mixture of speaker traits and content. This paper proposes a …

In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …