The state-of-the-art speaker recognition systems are usually trained on a single computer using speech data collected from multiple users. However, these samples may contain private information which users not be willing to share. To overcome potential breaches of privacy, we investigate the use federated learning with and without secure aggregators both for supervised unsupervised systems. Fed...

Using biometrics to verify a person’s identity has several advantages such as avoid practice of passwords. Speaker recognition is the process of recognize a people using speaker-specific information contained in a speech signal. Speaker recognition systems can be divided into two modes: identify a particular person or verify a person’s based on claimed identity. Front-end and back-end processin...

This paper gives an overview of automatic speaker recognition technology, with an emphasis on text-independent recognition. Speaker recognition has been studied actively for several decades. We give an overview of both the classical and the state-of-the-art methods. We start with the fundamentals of automatic speaker recognition, concerning feature extraction and speaker modeling. We elaborate ...

1. Abstract 2. Introduction 3. Behavioural studies 3.1. Perceptual differences between speakers 3.2. Recognition of unfamiliar speakers 3.3. Recognition of familiar speakers 4. Neural mechanisms of speaker recognition 4.1. Clinical studies 4.2. Voice selectivity 4.3. Processing of GPR and VTL 4.4. Processing of speaker identity 4.5. Unfamiliar versus familiar speakers 4.6. Integration of speake...

We present the principle of trajectory space comparison for text-independent speaker recognition and some solutions to the space comparison problem based on vector quantization. The comparison of recognition rate of diierent solutions is reported. Experimental system achieved 99.5% text-independent speaker recognition rate for 23 speakers, using 5 phrases for training and 5 for test. A speaker-...