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java.lang.Objectedu.cmu.sphinx.result.MAPConfidenceScorer
public class MAPConfidenceScorer
Computes confidences for the highest scoring path in a Result. The highest scoring path refers to the path with the
maximum a posteriori (MAP) probability, which is why this class is so named. Note that this MAPConfidenceScorer
creates a Lattice
from the result first, which means that you should only use this
confidence scorer if the result is created from the LexTreeLinguist
and the
WordPruningBreadthFirstSearchManager
.
Field Summary | |
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static java.lang.String |
PROP_DUMP_LATTICE
Sphinx property that specifies whether to dump the lattice. |
static java.lang.String |
PROP_DUMP_SAUSAGE
Sphinx property that specifies whether to dump the sausage. |
static java.lang.String |
PROP_LANGUAGE_WEIGHT
Sphinx property that defines the language model weight. |
Constructor Summary | |
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MAPConfidenceScorer()
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Method Summary | |
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void |
newProperties(PropertySheet ps)
This method is called when this configurable component needs to be reconfigured. |
ConfidenceResult |
score(Result result)
Computes confidences for a Result and returns a ConfidenceResult, a compact representation of all the hypothesis contained in the result together with their per-word and per-path confidences. |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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@S4Double(defaultValue=1.0) public static final java.lang.String PROP_LANGUAGE_WEIGHT
@S4Boolean(defaultValue=false) public static final java.lang.String PROP_DUMP_LATTICE
@S4Boolean(defaultValue=false) public static final java.lang.String PROP_DUMP_SAUSAGE
Constructor Detail |
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public MAPConfidenceScorer()
Method Detail |
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public void newProperties(PropertySheet ps) throws PropertyException
Configurable
newProperties
in interface Configurable
ps
- a property sheet holding the new data
PropertyException
- if there is a problem with the properties.public ConfidenceResult score(Result result)
score
in interface ConfidenceScorer
result
- the result to compute confidences for
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