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A Novel Scheme for Speaker Recognition Using a Phonetically-Aware Deep Neural Network

https://doi.org/10.21236/ada613971
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FedSP: Federated Speaker Verification with Personal Privacy Preservation
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Bottleneck Based Front-End for Diarization Systems
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Prioritized Grid Highway Long Short-Term Memory-Based Universal Background Model for Speaker Verification
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Optimized Active Learning Strategy for Audiovisual Speaker Recognition
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Collaborative Learning for Language and Speaker Recognition
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Sparse Coding of Bottleneck Features-Based i-Vector Representation for Language Recognition
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Investigating i-Vector Framework for Speaker Verification in Wild Conditions
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Improvement of Speaker Verification Using Deep Learning Techniques
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CNN-Based Audio Word Comparison: Exploring MobileNet for Similarity Assessment
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Speaker discrimination based on fuzzy fusion and feature reduction techniques
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A deep learning approach for speaker recognition
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Short-utterance speaker verification using deep learning
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Offline to online speaker adaptation for real-time deep neural network based LVCSR systems
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Dysarthria severity assessment using squeeze-and-excitation networks
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Deep neural network based i-vector mapping for speaker verification using short utterances
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Machine Learning for Speaker Recognition
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Preface
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Introduction
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Learning Algorithms
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Machine Learning Models
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Deep Learning Models
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Robust Speaker Verification
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Domain Adaptation
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Dimension Reduction and Data Augmentation
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Future Direction
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Exercises
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Index
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Voice conversion versus speaker verification: an overview
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Speaker verification with short utterances: a review of challenges, trends and opportunities
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Deep CNNs With Self-Attention for Speaker Identification
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Subtraction-Positive Similarity Learning
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Phonetic-Attention Scoring for Deep Speaker Features in Speaker Verification
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End-to-end text-independent speaker verification with flexibility in utterance duration
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Improving native language (L1) identifation with better VAD and TDNN trained separately on native and non-native English corpora
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CNN with Phonetic Attention for Text-Independent Speaker Verification
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Person Voice Recognition Methods
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Joint Bayesian Gaussian Discriminant Analysis for speaker verification
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inferred← citeshttps://doi.org/10.21437/interspeech.2017-203openalex-snapshot
The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016
inferred← citeshttps://doi.org/10.21437/interspeech.2017-301openalex-snapshot
Longitudinal Speaker Clustering and Verification Corpus with Code-Switching Frisian-Dutch Speech
inferred← citeshttps://doi.org/10.21437/interspeech.2017-44openalex-snapshot
End-to-End Language Identification Using High-Order Utterance Representation with Bilinear Pooling
inferred← citeshttps://doi.org/10.21437/interspeech.2017-452openalex-snapshot
Deep Speaker Feature Learning for Text-Independent Speaker Verification
inferred← citeshttps://doi.org/10.21437/interspeech.2018-1685openalex-snapshot
Robust and Discriminative Speaker Embedding via Intra-Class Distance Variance Regularization
inferred← citeshttps://doi.org/10.21437/interspeech.2018-1929openalex-snapshot
VoxCeleb2: Deep Speaker Recognition
inferred← citeshttps://doi.org/10.21437/interspeech.2018-993openalex-snapshot
Attentive Statistics Pooling for Deep Speaker Embedding
inferred← citeshttps://doi.org/10.21437/interspeech.2019-1444openalex-snapshot
Auto-Encoding Nearest Neighbor i-Vectors for Speaker Verification
inferred← citeshttps://doi.org/10.21437/interspeech.2019-2177openalex-snapshot
Spatial Pyramid Encoding with Convex Length Normalization for Text-Independent Speaker Verification
inferred← citeshttps://doi.org/10.21437/interspeech.2019-3116openalex-snapshot
Who Said That?: Audio-Visual Speaker Diarisation of Real-World Meetings
inferred← citeshttps://doi.org/10.21437/interspeech.2020-2026openalex-snapshot
Defense for Black-Box Attacks on Anti-Spoofing Models by Self-Supervised Learning
inferred← citeshttps://doi.org/10.21437/interspeech.2021-1167openalex-snapshot
Additive Phoneme-Aware Margin Softmax Loss for Language Recognition
inferred← citeshttps://doi.org/10.21437/interspeech.2022-885openalex-snapshot
Learning Lip-Based Audio-Visual Speaker Embeddings with AV-HuBERT
inferred← citeshttps://doi.org/10.21437/interspeech.2023-1648openalex-snapshot
Describing the phonetics in the underlying speech attributes for deep and interpretable speaker recognition
inferred← citeshttps://doi.org/10.21437/odyssey.2016-30openalex-snapshot
LID-senone Extraction via Deep Neural Networks for End-to-End Language Identification
inferred← citeshttps://doi.org/10.21437/odyssey.2016-36openalex-snapshot
Multi-channel i-vector combination for robust speaker verification in multi-room domestic environments
inferred← citeshttps://doi.org/10.21437/odyssey.2016-53openalex-snapshot
From Features to Speaker Vectors by means of Restricted Boltzmann Machine Adaptation
inferred← citeshttps://doi.org/10.21437/odyssey.2018-11openalex-snapshot
Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition System
inferred← citeshttps://doi.org/10.21437/odyssey.2018-46openalex-snapshot
How to train your speaker embeddings extractor
inferred← citeshttps://doi.org/10.21437/odyssey.2018-51openalex-snapshot
A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker Verification
inferred← citeshttps://doi.org/10.21437/odyssey.2020-2openalex-snapshot
BERTphone: Phonetically-aware Encoder Representations for Utterance-level Speaker and Language Recognition
inferred← citeshttps://doi.org/10.21437/odyssey.2020-3openalex-snapshot
Orthogonality Regularizations for End-to-End Speaker Verification
inferred← citeshttps://doi.org/10.21437/odyssey.2020-30openalex-snapshot
Learning Mixture Representation for Deep Speaker Embedding Using Attention
inferred← citeshttps://doi.org/10.21437/odyssey.2022-2openalex-snapshot
Analyzing Speaker Verification Embedding Extractors and Back-Ends Under Language and Channel Mismatch
inferred← citeshttps://doi.org/10.21437/spsc.2022-6openalex-snapshot
Adversarial speaker distillation for countermeasure model on automatic speaker verification
inferred← citeshttps://doi.org/10.23919/apsipa.2018.8659595openalex-snapshot
Deep Speaker Embeddings with Convolutional Neural Network on Supervector for Text-Independent Speaker Recognition
inferred← citeshttps://doi.org/10.23919/apsipa.2018.8659790openalex-snapshot
Investigation of Frame Alignments for GMM-based Digit-prompted Speaker Verification
inferred← citeshttps://doi.org/10.23919/eusipco47968.2020.9287363openalex-snapshot
Recognition of Actions and Subjects from Inertial and FSR Sensors Attached to Objects
inferred← citeshttps://doi.org/10.32657/10356/166407openalex-snapshot
Improving end-to-end transformer model architecture in ASR
inferred← citeshttps://doi.org/10.32657/10356/168498openalex-snapshot
Enhancing spoken language identification and diarization for multilingual speech
inferred← citeshttps://doi.org/10.3311/ppee.17024openalex-snapshot
Deep Learning Methods in Speaker Recognition: A Review
inferred← citeshttps://doi.org/10.3390/app9132761openalex-snapshot
Restricted Boltzmann Machine Vectors for Speaker Clustering and Tracking Tasks in TV Broadcast Shows
inferred← citeshttps://doi.org/10.3390/app9183697openalex-snapshot
An Analysis of the Short Utterance Problem for Speaker Characterization
inferred← citeshttps://doi.org/10.3390/e20080600openalex-snapshot
Identity Vector Extraction by Perceptual Wavelet Packet Entropy and Convolutional Neural Network for Voice Authentication
inferred← citeshttps://doi.org/10.3726/978-3-653-05777-5openalex-snapshot
Individual Differences in Speech Production and Perception
inferred← citeshttps://doi.org/10.4218/etrij.2021-0377openalex-snapshot
Variational autoencoder for prosody‐based speaker recognition
inferred← citeshttps://doi.org/10.47749/t/unicamp.2018.1089841openalex-snapshot
Deep-learning segmentation for skin lesion images
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