Automation of prediction system for temporal data

Singh, Brijendra; Jaiswal, Rashi

doi:10.1007/s41870-022-01065-x

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2023

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“…( 4 ), but also from output cell to input cell in the backward direction using Eq. ( 5 ), via two different hidden layers [ 38 ], inorder to preserve previous and future information as depicted in Fig. 3 b.…”

Section: Proposed System Overviewmentioning

confidence: 99%

Closed-set automatic speaker identification using multi-scale recurrent networks in non-native children

Radha

Bansal

2023

Int. j. inf. tecnol.

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Children may benefit from automatic speaker identification in a variety of applications, including child security, safety, and education. The key focus of this study is to develop a closed-set child speaker identification system for non-native speakers of English in both text-dependent and text-independent speech tasks in order to track how the speaker’s fluency affects the system. The multi-scale wavelet scattering transform is used to compensate for concerns like the loss of high-frequency information caused by the most widely used mel frequency cepstral coefficients feature extractor. The proposed large-scale speaker identification system succeeds well by employing wavelet scattered Bi-LSTM. While this procedure is used to identify non-native children in multiple classes, average values of accuracy, precision, recall, and F-measure are being used to assess the performance of the model in text-independent and text-dependent tasks, which outperforms the existing models.

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Section: Proposed System Overviewmentioning

confidence: 99%