8.1 Laplace (Add-one Smoothing) | Advanced Smoothing Models | Speech & Natural Language Processing

This lecture is part of a lecture series on Speech & Natural Language Processing given by Mr. Lalit Singh for B.Tech students at Binary Institute.
Description
This video explains Laplace smoothing, also known as add-one smoothing, a simple yet effective technique used in probabilistic language models within speech and natural language processing. It describes how Laplace smoothing works by adding one to the count of each word or n-gram, preventing zero probabilities for unseen events. The video covers the mathematical formulation, advantages, and limitations of this approach, along with examples of its application in text prediction and classification tasks. It also highlights why Laplace smoothing, while easy to implement, is often less accurate compared to more advanced smoothing techniques.

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