[PDF][PDF] Deep neural network embeddings for text-independent speaker verification.

D Snyder, D Garcia-Romero, D Povey, S Khudanpur - Interspeech, 2017 - isca-archive.org
This paper investigates replacing i-vectors for text-independent speaker verification with
embeddings extracted from a feedforward deep neural network. Long-term speaker …

Deep neural network-based speaker embeddings for end-to-end speaker verification

D Snyder, P Ghahremani, D Povey… - 2016 IEEE spoken …, 2016 - ieeexplore.ieee.org
In this study, we investigate an end-to-end text-independent speaker verification system. The
architecture consists of a deep neural network that takes a variable length speech segment …

Speaker diarization using deep neural network embeddings

D Garcia-Romero, D Snyder, G Sell… - … , Speech and Signal …, 2017 - ieeexplore.ieee.org
Speaker diarization is an important front-end for many speech technologies in the presence
of multiple speakers, but current methods that employ i-vector clustering for short segments …

State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and speakers in the wild evaluations

J Villalba, N Chen, D Snyder, D Garcia-Romero… - Computer Speech & …, 2020 - Elsevier
We present a thorough analysis of the systems developed by the JHU-MIT consortium in the
context of NIST speaker recognition evaluation 2018. In the previous NIST evaluation, in …

Analyzing noise robustness of MFCC and GFCC features in speaker identification

X Zhao, DL Wang - … conference on acoustics, speech and signal …, 2013 - ieeexplore.ieee.org
Automatic speaker recognition can achieve a high level of performance in matched training
and testing conditions. However, such performance drops significantly in mismatched noisy …

Deep feature for text-dependent speaker verification

Y Liu, Y Qian, N Chen, T Fu, Y Zhang, K Yu - Speech Communication, 2015 - Elsevier
Recently deep learning has been successfully used in speech recognition, however it has
not been carefully explored and widely accepted for speaker verification. To incorporate …

[PDF][PDF] Language recognition in ivectors space

D Martinez, O Plchot, L Burget, O Glembek… - … annual conference of …, 2011 - isca-archive.org
The concept of so called iVectors, where each utterance is represented by fixed-length low-
dimensional feature vector, has recently become very successfully in speaker verification. In …

PLDA for speaker verification with utterances of arbitrary duration

P Kenny, T Stafylakis, P Ouellet… - … , Speech and Signal …, 2013 - ieeexplore.ieee.org
The duration of speech segments has traditionally been controlled in the NIST speaker
recognition evaluations so that researchers working in this framework have been relieved of …

PLDA based speaker recognition on short utterances

A Kanagasundaram, R Vogt, D Dean… - Proceedings of The …, 2012 - eprints.qut.edu.au
This paper investigates the effects of limited speech data in the context of speaker
verification using a probabilistic linear discriminant analysis (PLDA) approach. Being able to …

Golden Gemini is All You Need: Finding the Sweet Spots for Speaker Verification

T Liu, KA Lee, Q Wang, H Li - IEEE/ACM Transactions on Audio …, 2024 - ieeexplore.ieee.org
The residual neural networks (ResNet) demonstrate the impressive performance in
automatic speaker verification (ASV). They treat the time and frequency dimensions equally …