Results 21 to 30 of about 3,069 (260)
On Residual CNN in Text-Dependent Speaker Verification Task [PDF]
, 2017 Deep learning approaches are still not very common in the speaker verification field. We investigate the possibility of using deep residual convolutional neural network with spectrograms as an input features in the text-dependent speaker verification task.
Egor Malykh +2 more
openaire +2 more sources
Utterance Verification for Text-Dependent Speaker Recognition:A Comparative Assessment Using the RedDots Corpus [PDF]
, 2016 Text-dependent automatic speaker verification naturally calls for the simultaneous verification of speaker identity and spoken content. These two tasks can be achieved with automatic speaker verification (ASV) and utterance verification (UV) technologies.
Kukanov, Ivan +22 more
core +1 more source
Exploiting sequence information for text-dependent Speaker Verification [PDF]
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 Model-based approaches to Speaker Verification (SV), such as Joint Factor Analysis (JFA), i-vector and relevance Maximum-a-Posteriori (MAP), have shown to provide state-of-the-art performance for text-dependent systems with fixed phrases. The performance of i-vector and JFA models has been further enhanced by estimating posteriors from Deep Neural ...
Subhadeep Dey +3 more
openaire +1 more source
Attention-Based Models for Text-Dependent Speaker Verification [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 Submitted to ICASSP ...
F. A. Rezaur Rahman Chowdhury +3 more
openaire +2 more sources
Employing Emotion Cues to Verify Speakers in Emotional Talking Environments
Journal of Intelligent Systems, 2016 Usually, people talk neutrally in environments where there are no abnormal talking conditions such as stress and emotion. Other emotional conditions that might affect people’s talking tone include happiness, anger, and sadness. Such emotions are directly
Shahin Ismail
doaj +1 more source
DEEP NEURAL NETWORKS FOR SMALL FOOTPRINT TEXT-DEPENDENT SPEAKER VERIFICATION [PDF]
, 2014 In this paper we investigate the use of deep neural networks (DNNs) for a small footprint text-dependent speaker verification task. At de-velopment stage, a DNN is trained to classify speakers at the frame-level.
Erik Mcdermott +4 more
core +1 more source
上海师范大学学报. 自然科学版, 2016 A text-dependent i-vector extraction scheme and a lexicon-based binary vector (L-vector) representation are proposed to improve the performance of text-dependent speaker verification.An utterance used for enrollment or test is represented by these two ...
LI Wei, YOU Hanxu, ZHU Jie, CHEN Ning
doaj +1 more source
Constrained temporal structure for text-dependent speaker verification [PDF]
Digital Signal Processing, 2013 In the context of mobile devices, speaker recognition engines may suffer from ergonomic constraints and limited amount of computing resources. Even if they prove their efficiency in classical contexts, GMM/UBM systems show their limitations when restricting the quantity of speech data.
Anthony Larcher +2 more
openaire +1 more source
Lexicon-Based Local Representation for Text-Dependent Speaker Verification
IEICE Transactions on Information and Systems, 2017 YOU, Hanxu +3 more
exaly +3 more sources
Effects of gender information in text-independent and text-dependent speaker verification [PDF]
, 2017 It is well-known that for speaker recognition task, gender-dependent acoustic modeling performs better than gender-independent modeling. The practice is to use the gender ground-truth and to train gender-dependent models. However, such information is not
Md Sahidullah +9 more
core +1 more source