2006 Document Image Decoding (DID) vs. Hidden Markov Models (HMM)

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    2006 Document Image Decoding (DID) vs. Hidden Markov Models (HMM) - Presentation Transcript

    1. Motivation ● quick talk that I had sitting around ● originally: 2001, but relevant today – HMM/OCR work at Google ● not a polished talk ● no punchline
    2. Overview ● problem: “input signal” → transcription – signal: speech, line of printed or handwritten text ● properties – input signal generated from sequence of symbols ● speech: phonemes ● handwriting/OCR: characters – symbols correspond to “segments” of input – segments are linearly arranged – segments are noisy – output represents a valid sentence in natural language – often know even more about the output (domain of discourse, etc.)

    + Thomas BreuelThomas Breuel, 2 years ago

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