Speech Recognition
Speech recognition (speech-to-text) converts spoken audio into written text, so machines can understand and act on what people say.
In Simple Terms
Think of it as a very fast stenographer who turns talk into text.
Detailed Explanation
Speech recognition uses acoustic and language models to transcribe or caption live or recorded audio. It is used in assistants, captioning, and voice-controlled apps. When to use it: for hands-free input, accessibility, or when the primary input is voice. Common mistakes: assuming it works equally well for all accents and environments, or skipping punctuation and formatting controls.
Related Terms
RAG
Retrieval-Augmented Generation combines AI models with external knowledge retrieval for accurate responses.
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Deep learning is machine learning using neural networks with many layers. Depth allows models to learn hierarchical representations and has driven breakthroughs in vision, language, and other domains.
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Sentiment analysis is the use of NLP and often ML to detect the emotional tone or opinion in text (e.g., positive, negative, neutral). It is used in feedback, social listening, and customer insight.
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