Speaker recognition is the identification of the person who is speaking by characteristics of their voices, also called “voice recognition”. The components of Speaker Recognition includes Speaker Identification(SI) and Speaker Verification(SV). Speaker identification is the task of determining an unknown speakers identity. If the speaker claims to be of a certain identity and the voice is to ve...

This paper focuses on speaker detection using multispeaker files both for the enrollment phase and for the test phase. This task was introduced during the 2002 NIST speaker recognition evaluation campaign. Enrollment data is composed of three two-speaker files. Test files are also two-speaker records. The system presented here uses a speaker segmentation process based on an HMM conversation mod...

A system for speaker tracking in broadcast-news audio data is presented and the impacts of the main components of the system to the overall speaker-tracking performance are evaluated. The process of speaker tracking in continuous audio streams involves several processing tasks and is therefore treated as a multistage process. The main building blocks of such system include the components for au...

The performance of speaker verification system degrades when the test segments are utterances of short duration, therefore, we investigate the use of model representing our target speaker with his close speaker and his own speech data. We propose to create a new Speaker Model who groups close speakers (CS) achieved with two clustering algorithms in Automatic Speaker Verification A.S.V. Intra an...

This paper presents Cisco’s speaker segmentation and recognition (SSR) system, which is a part of a commercial product. Cisco SSR uses speaker segmentation and speaker recognition algorithms with a crowd sourcing approach to create speaker metadata. The speaker metadata makes the enterprise videos more accessible and more navigable by itself, and by its combination with other forms of metadata ...

This dissertation addresses the independence of observations assumption which is typically made by today’s automatic speech recognition systems. This assumption ignores within-speaker correlations which are known to exist. The assumption clearly damages the recognition ability of standard speaker independent systems, as can seen by the severe drop in performance exhibited by systems between the...