… It also addresses a lack of ethnic diversity in the VoxCeleb1 dataset (section 3); (ii) we propose
deep ResNet-based architectures for speaker embedding suitable for spectrogram inputs …

… speakers voice samples as a input for recognition purpose. Main goal of this work is to obtain
better accuracy for speaker recognition system for large number of voice database. In this …

… The leaves represent exclusive partitions of the input data. A test vector will be evaluated at
each node and directed to one of two subsequent nodes based on a decision. This decision …

… In the text-independent case, there is no restriction on the sentence or phrase to be spoken,
whereas in the text-dependent case, the input sentence or phrase is fixed for each speaker. …

… representations of unlabelled input data. In (Banerjee et al., 2018), spectrograms (25 ms
window size, 10 ms timestep) have been fed as input speech data after applying PCA …

… After the enrolment session, the acoustic vectors extracted from input speech of a speaker
… In this work, the utterances of several speakers are taken and the data are divided in music (…

… where R, is the autocorrelation matrix of speech input data associated with the vector a. Using
this distortion measure, and the VQ codebook training algorithm proposed by Linde, Buzo, …

… Then the likelihood of input … databases designed for speaker recognition and related areas
include KING corpus and SWITCHBOARD corpus [24]. It is crucial to extend these databases …

… To remove the non-speech portions from input data, an energy based voice activity detector
with fixed threshold was used. The cepstral mean subtraction was applied on all features so …

… of the computed input feature vectors to models of the claimed speaker or feature vector …
to a representation problem, we seek other means to reduce the dimensionality of the data. …