Deep Dive
Introduction to NLP
The lecture begins with an overview of Natural Language Processing (NLP), a branch of AI that enables computers to understand, interpret, and generate human language. It explains how computers, fundamentally designed to work with numbers, use NLP to convert human language into a processable form.
Understanding Human Language
The complexity of human language is highlighted, focusing on how the same word can have different meanings depending on context. Examples like 'bank' illustrate the need for context in understanding language. The process involves breaking down sentences into tokens and converting them into numerical representations.
NLP Processes
The lecture details the NLP process, including pre-processing, tokenization, and numerical representation. It explains how text is cleaned and divided into tokens, which are then converted into numerical vectors that computers can process.
Challenges in Speech Recognition
Challenges in speech recognition are discussed, such as background noise and accents affecting clarity. The system must separate useful speech from noise and handle different pronunciations of words to accurately recognize speech.
Advanced NLP Techniques
Modern NLP systems rely on transformer architecture and attention mechanisms to understand context. These systems determine which tokens are important when processing a sentence, allowing for more accurate interpretation of language.