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Speech production under uncertainty: how do job
applicants experience and communicate with an AI
interviewer?
Theories and research in human–machine communication (HMC) suggest that machines, when replacing humans as communication partners,
change the processes and outcomes of communication. With artificial intelligence (AI) increasingly used to interview…
change the processes and outcomes of communication. With artificial intelligence (AI) increasingly used to interview…
Speech Enhancement and Recognition using Kalman Filter Modified via Radial Basis Function
In this paper, a Radial Basis Function-based Kalman filter has been utilized to perform speech enhancement of an audio signal. Moreover, in order to accomplish speech recognition, correlation after detecting signal envelop has been applied. Based on…
Special allocation fund (DAK) for education sector: a development policy evaluation perspective
National development in education is essentially carried out in order to improve the quality of human resources. In practice, this is established in a series of programs and activities involving the central and regional governments related to…
Speaker Identification Using a Convolutional Neural Network
Speech, a mode of communication between humans and machines, has various applications, including biometric systems for
identifying people have access to secure systems. Feature extraction is an important factor in speech recognition with high…
identifying people have access to secure systems. Feature extraction is an important factor in speech recognition with high…
Speaker Identification Using a Convolutional Neural Network
Speech, a mode of communication between humans and machines, has various applications, including biometric systems for
identifying people have access to secure systems. Feature extraction is an important factor in speech recognition with high…
identifying people have access to secure systems. Feature extraction is an important factor in speech recognition with high…
spBayesSurv: Fitting Bayesian Spatial Survival Models Using R
Spatial survival analysis has received a great deal of attention over the last 20 years
due to the important role that geographical information can play in predicting survival.
This paper provides an introduction to a set of programs for…
due to the important role that geographical information can play in predicting survival.
This paper provides an introduction to a set of programs for…
sparsegl: An R Package for Estimating Sparse Group Lasso
The sparse group lasso is a high-dimensional regression technique that is useful for
problems whose predictors have a naturally grouped structure and where sparsity is encouraged at both the group and individual predictor level. In this paper we…
problems whose predictors have a naturally grouped structure and where sparsity is encouraged at both the group and individual predictor level. In this paper we…
Spare Parts Demand Forecasting During Covid 19 pandemic(Automotive Company Case Study)
The research was conducted to analyze the calculation of demand forecasting and inventory of spare parts . The data collection method uses descriptive quantitative by conducting literature studies, interviews, and collecting sample …
SPAMMER DETECTION BASED ON ACCOUNT, TWEET, AND COMMUNITY ACTIVITY ON TWITTER
Spammers are the activities of users who abuse Twitter to spread spam. Spammers imitate legitimate user behavior patterns to avoid being detected by spam detectors. Spammers create lots of fake accounts and collaborate with each other to form…
Spam Detection in Emails Using Machine Learning Techniques: A Review
Despite the vast amounts of data available within email communication systems, spam remains a persistent issue, posing challenges for both users and organizations. Analyzing this data holds the potential to develop more effective methods for…