A Novel Convolutional Neural Network Model for Automatic Speaker Identification From Speech Signals

Since voice communication is the most frequent form of human communication, it is necessary to identify each speaker in a discussion. The development of advanced computer processing units, deep learning techniques and publicly available datasets prompt the need for proposing novel automated speaker...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.51381-51394
Hauptverfasser:	Pandian, J. Arun, Thirunavukarasu, Ramkumar, Kotei, Evans
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks audio data augmentation Audio signal classification Classification Convolution convolutional neural network Convolutional neural networks Datasets Deep learning English language Feature extraction Human communication Machine learning Mel frequency cepstral coefficient Neural networks Random noise speaker identification Spectrogram spectrogram signals Speech recognition Stretching Task analysis Voice communication white Gaussian noise
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