Text-dependent speaker verification system: A review

Debnath, Saswati; Soni, Badal; Baruah, Ujwala; Kumar, Sunil

doi:10.1109/isco.2015.7282386

Cited by 13 publications

(3 citation statements)

References 16 publications

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“…Cloud computing acquired tremendous popularity in recent years, mainly due to advancements in virtualization technology. This technology has shown a new era to many applications that applies speech and signal processing (1,2) with 5g, (3) which provides higher bandwidth and flexibility. To get pay-per-use services, many applications were forwarded to data centers.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation on periotity based schuduling and improve the security using DSSHA-256

Prathap Kumar,

Rohini

2024

Data and Metadata

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Cloud computing has gained popularity with advancements in virtualization technology and the deployment of 5G. However, scheduling workload in a heterogeneous multi-cloud environment is a complicated process. Users of cloud services want to ensure that their data is secure and private, especially sensitive or proprietary information. Several research works have been proposed to solve the challenges associated with cloud computing. The proposed Adaptive Priority based scheduling (PBS) focuses on reducing data access completion time and computation expense for task scheduling in cloud computing. PBS assigns tasks depending on its size and selects the minimum cost path for data access. It contains a task register, scheduler, and task execution components for efficient task execution. The proposed system also executes a double signature mechanism for data privacy and security in data storage. This study correlates the perfo}rmance of three algorithms, PBS, (Task Requirement Degree) TRD and (recommended a Risk adaptive Access Control) RADAC, in terms of task execution time and makespan time. The experimental results demonstrate that PBS outperforms TRD and RADAC in both metrics, as the number of tasks increases. PBS has a minimum task execution time and a lower makespan time than the othertwo algorithms

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Section: Introductionmentioning

confidence: 99%

Resource allocation on periotity based schuduling and improve the security using DSSHA-256

Prathap Kumar,

Rohini

2024

Data and Metadata

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“…The latest advances in virtualization technology have elevated it to a significant position currently. Cloud computing has given new life to a wide range of applications, including speech and signal processing [ 1 , 2 ], thanks to the increased bandwidth and flexibility provided by 5G [ 3 ]. A variety of applications are submitted to data centers to obtain pay-per-use services.…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Strategy and Secure VM Placement Algorithm in Cloud Computing

Srivastava

Tiwari

Srivastava

et al. 2022

Computational Intelligence and Neuroscience

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One of the important and challenging tasks in cloud computing is to obtain the usefulness of cloud by implementing several specifications for our needs, to meet the present growing demands, and to minimize energy consumption as much as possible and ensure proper utilization of computing resources. An excellent mapping scheme has been derived which maps virtual machines (VMs) to physical machines (PMs), which is also known as virtual machine (VM) placement, and this needs to be implemented. The tremendous diversity of computing resources, tasks, and virtualization processes in the cloud causes the consolidation method to be more complex, tedious, and problematic. An algorithm for reducing energy use and resource allocation is proposed for implementation in this article. This algorithm was developed with the help of a Cloud System Model, which enables mapping between VMs and PMs and among tasks of VMs. The methodology used in this algorithm also supports lowering the number of PMs that are in an active state and optimizes the total time taken to process a set of tasks (also known as makespan time). Using the CloudSim Simulator tool, we evaluated and assessed the energy consumption and makespan time. The results are compiled and then compared graphically with respect to other existing energy-efficient VM placement algorithms.

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“…Therefore, in order to achieve the optimum performance, the input signals must contain as many clean speech segments as possible, while simultaneously discarding low information segments (i.e., silence, noise, noise-corrupted speech). To accomplish this, many speaker recognition systems utilize a speech activity detector (SAD) as the first step in the process to select frames from the presented signal that contain speech [Debnath et al, 2015;Kumar et al, 2017]. Typically the SAD will utilize speech parameters such as signal energy, long-term spectral divergence, or melfrequency cepstrum coefficients (MFCCs) to make a decision whether or not speech is present [Asgari et al, 2008].…”

Section: Introductionmentioning

confidence: 99%

Approximate Entropy and Empirical Mode Decomposition for Improved Speaker Recognition

Metzger

Doherty

Jenkins

et al. 2020

Adv. Data Sci. Adapt. Data Anal.

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When processing real-world recordings of speech, it is highly probable noise will be present at some instance in the signal. Compounding this problem is the situation when the noise occurs in short, impulsive bursts at random intervals. Traditional signal processing methods used to detect speech rely on the spectral energy of the incoming signal to make a determination whether or not a segment of the signal contains speech. However when noise is present, this simple energy detection is prone to falsely flagging noise as speech. This paper will demonstrate an alternative way of processing a noisy speech signal utilizing a combination of information theoretic and signal processing principles to differentiate speech segments from noise. The utilization of this preprocessing technique will allow a speaker recognition system to train statistical speaker model using noise-corrupted speech files, and construct models statistically similar to those constructed from noise-free data. This preprocessing method will be shown to outperform traditional spectrum-based methods for both low-entropy and high-entropy noise in low signal-to-noise ratio environments, with a reduction in the feature space distortion when measured using the Cauchy–Schwarz (CS) distance metric.

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Text-dependent speaker verification system: A review

Cited by 13 publications

References 16 publications

Resource allocation on periotity based schuduling and improve the security using DSSHA-256

Resource allocation on periotity based schuduling and improve the security using DSSHA-256

An Energy-Efficient Strategy and Secure VM Placement Algorithm in Cloud Computing

Approximate Entropy and Empirical Mode Decomposition for Improved Speaker Recognition

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