{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/speech-recognition",
  "headline": "Speech Recognition: From HMMs to Whisper",
  "description": "Speech recognition converts audio signals to text. Modern end-to-end approaches — CTC, RNN-Transducer, Attention-based Encoder-Decoder — have replaced traditional HMM-GMM pipelines, with Whisper achieving near-human performance.",
  "dateCreated": "2026-05-24T02:49:13.661Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Robust Speech Recognition via Large-Scale Weak Supervision (Whisper)",
      "sameAs": "https://arxiv.org/abs/2212.04356"
    },
    {
      "@type": "CreativeWork",
      "name": "Connectionist Temporal Classification",
      "sameAs": "https://www.cs.toronto.edu/~graves/icml_2006.pdf"
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}