Machine learning approaches to analyzing public speaking and vocal delivery

The 21st century has ushered in a wave of technological advancements, notably machine learning, with profound implications for the analysis public speaking and vocal delivery. This literature review scrutinizes deployment learning techniques evaluation enhancement skills, critical facet effective communication across various professions everyday contexts.
 exploration begins an examination models such as Support Vector Machines, Convolutional Neural Networks, Long Short-Term Memory models. These models' application non-verbal speech features, emotion detection, performance offers promising avenue objective, scalable, efficient analysis, surpassing limitations traditional, often subjective, methods.
 discussion extends to real-world these techniques, encompassing skill teacher delivery evaluation, assessment anxiety. Various frameworks are presented, emphasizing their effectiveness generating large-scale, objective results.
 However, discourse acknowledges challenges inherent technologies, including data privacy concerns, potential over-reliance on technology, necessity diverse extensive datasets. drawbacks approaches highlighted, underscoring need further research address issues.
 Despite challenges, successes numerous applications this field underscored, along future advancements. By dissecting past failures, aims provide guidance more technologies future, contributing ongoing efforts revolutionize