Theoretical Analysis of Machine Learning Paradigms In Voice Search Optimization

Additionally, voice search optimization is a dynamic process because it takes into account the sophistication and persistence of constantly evolving societal issues and Social Media Analytics human behavior. Different machine learning strategies are required to deal with this dynamism. As a result, ensemble learning and transfer learning are becoming the focus of research efforts. Multiple models are combined in ensemble learning to produce better predictive performance. Transfer learning, on the other hand, demonstrates significant promise in handling low-resource languages in voice search systems by utilizing the knowledge gained in one task to solve a different yet related task. ...........................................

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