ALIZE 3.0 - open source toolkit for state-of-the-art speaker recognition
نویسندگان
چکیده
ALIZE is an open-source platform for speaker recognition. The ALIZE library implements a low-level statistical engine based on the well-known Gaussian mixture modelling. The toolkit includes a set of high level tools dedicated to speaker recognition based on the latest developments in speaker recognition such as Joint Factor Analysis, Support Vector Machine, i-vector modelling and Probabilistic Linear Discriminant Analysis. Since 2005, the performance of ALIZE has been demonstrated in series of Speaker Recognition Evaluations (SREs) conducted by NIST and has been used by many participants in the last NISTSRE 2012. This paper presents the latest version of the corpus and performance on the NIST-SRE 2010 extended task.
منابع مشابه
ALIZE/spkdet: a state-of-the-art open source software for speaker recognition
This paper presents the ALIZE/SpkDet open source software packages for text independent speaker recognition. This software is based on the well-known UBM/GMM approach. It includes also the latest speaker recognition developments such as Latent Factor Analysis (LFA) and unsupervised adaptation. Discriminant classifiers such as SVM supervectors are also provided, linked with the Nuisance Attribut...
متن کاملA Speaker Verification System under the Scope: Alize
Title: A Speaker Verification System Under The Scope: Alize Automatic Speaker Recognition is the collective name for problems that involve identifying a person or verifying the identity of a person using her voice. The French speaker recognition toolkit Alize from University of Avignon has been explored from the viewpoint of a toolkit already in use at KTH, called GIVES. The exploration has aim...
متن کاملThe RWTH aachen university open source speech recognition system
We announce the public availability of the RWTH Aachen University speech recognition toolkit. The toolkit includes state of the art speech recognition technology for acoustic model training and decoding. Speaker adaptation, speaker adaptive training, unsupervised training, a finite state automata library, and an efficient tree search decoder are notable components. Comprehensive documentation, ...
متن کاملRASR – The RWTH Aachen University Open Source Speech Recognition Toolkit
RASR is the open source version of the well-proven speech recognition toolkit developed and used at RWTH Aachen University. The current version of the package includes state of the art speech recognition technology for acoustic model training and decoding. Speaker adaptation, speaker adaptive training, unsupervised training, discriminative training, lattice processing tools, flexible signal ana...
متن کاملApplication of automatic speaker recognition techniques to pathological voice assessment (dysphonia)
This paper investigates the adaptation of Automatic Speaker Recognition (ASR) techniques to the pathological voice assessment (dysphonic voices). The aim of this study is to provide a novel method, suitable for keeping track of the evolution of the patient’s pathology: easy-to-use, fast, non-invasive for the patient, and affordable for the clinicians. This method will be complementary to the ex...
متن کامل