Erratum to: Latent discriminative representation learning for speaker recognition
نویسندگان
چکیده
منابع مشابه
MLP Internal Representation as Discriminative Features for Improved Speaker Recognition
Feature projection by non-linear discriminant analysis (NLDA) can substantially increase classification performance. In automatic speech recognition (ASR) the projection provided by the pre-squashed outputs from a one hidden layer multi-layer perceptron (MLP) trained to recognise speech subunits (phonemes) has previously been shown to significantly increase ASR performance. An analogous approac...
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Due to the growing need for security applications speaker recognition as the biometric task of authenticating a claimant by voice has currently become a focus of interest. Traditionally approaches in the area of speaker recognition were mainly based on generative classi ers like Gaussian Mixture Models (GMMs). However, more recently other classi ers like Support Vector Machines (SVMs) have been...
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Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space between image and semantic representations. For years, among existing works, it has been the center task to learn the proper mapping matrices aligning the visual and semantic space, whilst the importance to learn discriminative representations for ZSL is ignored. In this work, we retrospect existin...
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Existing block-diagonal representation studies mainly focuses on casting block-diagonal regularization on training data, while only little attention is dedicated to concurrently learning both block-diagonal representations of training and test data. In this paper, we propose a discriminative block-diagonal low-rank representation (BDLRR) method for recognition. In particular, the elaborate BDLR...
متن کاملDesigning a speaker-discriminative adaptive filter bank for speaker recognition
A new filter bank approach for speaker recognition front-end is proposed. The conventional mel-scaled filter bank is replaced with a speaker-discriminative filter bank. Filter bank is selected from a library in adaptive basis, based on the broad phoneme class of the input frame. Each phoneme class is associated with its own filter bank. Each filter bank is designed in a way that emphasizes disc...
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ژورنال
عنوان ژورنال: Frontiers of Information Technology & Electronic Engineering
سال: 2021
ISSN: 2095-9184,2095-9230
DOI: 10.1631/fitee.19e0690