Real-time voice classification with Random Forest

In an era marked by the integration of advanced technologies into our daily lives, real-time voice classification systems have emerged as pivotal tools across various domains. The Python script in this section, showcasing the implementation of a real-time voice classification system using the Random Forest classifier from scikit-learn, is a testament to the versatility and significance of such applications.

The primary objective of this script is to harness the power of machine learning to differentiate between positive audio samples, indicative of human speech (voice), and negative samples, representing background noise or non-vocal elements. By employing the Random Forest classifier, a robust and widely used algorithm from the scikit-learn library, the script endeavors to create an efficient model capable of accurately classifying real-time audio input.

The real-world applications of this voice classification system are extensive...