Word Embeddings are a technique in NLP that represent words as continuous vectors in a high-dimensional space. These vectors capture semantic and syntactic relationships between words. Word embeddings are useful for tasks such as language translation, sentiment analysis, and document clustering.
Speech Recognition enables machines to understand and interpret spoken words. By applying natural language processing techniques and AI models, businesses can develop speech recognition…