We consider two approaches to DNN-based SID: one that uses the DNN to extract features, and another that uses the DNN during feature modeling. Modeling is ...
ABSTRACT. The recent application of deep neural networks (DNN) to speaker identification (SID) has resulted in significant improvements over.
This work considers two approaches to DNN-based SID: one that uses the DNN to extract features, and another that uses a DNN during feature modeling, ...
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... For speaker recognition, deep neural networks (DNNs) have successfully achieved state-of-the-art performance on challenging benchmarks, including SITW [13], ...
This paper summarizes the applied deep learning practices in the field of speaker recognition, both verification and identification. Speaker recognition has ...
In this paper, we review several major subtasks of speaker recognition, including speaker verification, identification, diarization, and robust speaker ...
Apr 6, 2015 · In this work we present the application of single DNN for both SR and LR using the 2013 Domain Adaptation Challenge speaker recognition (DAC13) ...
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Aug 17, 2022 · In this paper, we focus on the following speech processing tasks: automatic speech recognition, speaker identification, and emotion recognition.
In this paper, we present a review of the DL methodologies used for speaker identification and surveys important DL algorithms that can potentially be explored ...
The impressive gains in performance obtained using deep neural networks (DNNs) for automatic speech recognition (ASR) have motivated the application of DNNs ...