| Bayesian Approach |
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| • | Assume
a language model P(words) |
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| • | Want
P(words|signal). |
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| • | If we
had P(signal|words), we could compute the |
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| words
that maximize P(words|signal). How? |
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| • | If
the signal gave us a list of phones, we could do |
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| this,
but we can't. |
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| • | The
best we can do at this point is to compute |
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| P(words|phones). Then we need P(phones|signal). |
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| • | For
this, a hidden Markov model (HMM) is |
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| used. |
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