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...

On-line speaker indexing sequentially detects the points where a speaker identity changes in a multi-speaker audio stream, and classifies each speaker segment. This paper addresses two challenges: The first relates to monitoring which requires on-line processing. The second relates to the fact that the numberlidentity of the speakers is unknown. The indexing needs to be made in a unsupervised p...

This paper describes the speaker diarization systems proposed by the VIVOLAB-UZ group for the Albayzin 2010 speaker diarization evaluation. Our approaches combine recent improvements in the field of speaker segmentation in two speaker telephone conversations, using eigenvoice modeling, with the traditional Agglomerative Hierarchical Clustering approach. We are presenting two submissions. Our fi...

Voice cloning is a highly desired feature for personalized speech interfaces. Neural network based speech synthesis has been shown to generate high quality speech for a large number of speakers. In this paper, we introduce a neural voice cloning system that takes a few audio samples as input. We study two approaches: speaker adaptation and speaker encoding. Speaker adaptation is based on fine-t...

Speech signal contains several levels of information. At first it contains information about the spoken message. At second level speech signal also gives information about the speaker identity, his emotional state and so on. The task of speaker recognition can be divided into two parts: speaker identification and speaker verification. Speaker identification is answering the question which one o...