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__Speech__ The namespace containing the type interfaces of the library objects.
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__FuzzyMatcher__ Main use case for this library. Returns matches against a list of targets for a given query. The comparisions are not remembered and therefore better for one-off use cases.
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__EnPronouncer__ Pronounces a string, as a General English speaker, into its IPA string or array of Phones format.
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__AcceleratedFuzzyMatcher__ Same interface as `FuzzyMatcher` but the list of targets are precomputed, so beneficial for multiple queries at the cost of a higher initialization time.
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__matchers__ module:
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__EnPronouncer__ Pronounces a string, as a General English speaker, into its IPA string or array of Phones format.
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*__FuzzyMatcher__ Main use case for this library. Returns matches against a list of targets for a given query. The comparisions are not remembered and therefore better for one-off use cases.
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*__AcceleratedFuzzyMatcher__ Same interface as `FuzzyMatcher` but the list of targets are precomputed, so beneficial for multiple queries at the cost of a higher initialization time.
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*__EnContactMatcher__ A domain specialization of using the `AcceleratedFuzzyMatcher` for English speakers searching over a list of names. Does additional preprocessing and setups up the distance function for you.
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*__EnPlaceMatcher__ A domain specialization of using the `AcceleratedFuzzyMatcher` for English speakers searching over a list of places. Does additional preprocessing and setups up the distance function for you.
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__distance__ module:
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*__EnPhoneticDistance__ Returns a metric distance score between two English pronunciations.
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*__StringDistance__ Returns a metric distance score between two strings (edit distance).
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*__EnHybridDistance__ Returns a metric distance score based on a combination of the two above distance metrics (English pronunciations and strings).
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__EnPhoneticDistance__ Returns a metric distance score between two English pronunciations.
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*__DistanceInput__ Input object for EnHybridDistance. Hold the text and the pronunciation of that text
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__StringDistance__ Returns a metric distance score between two strings (edit distance).
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__nlp__ module:
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__EnHybridDistance__ Returns a metric distance score based on a combination of the two above distance metrics (English pronunciations and strings).
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*__EnPreProcessor__ English Pre-processor.
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*__EnPlacesPreProcessor__ English Pre-processor with specific rules for places.
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*__SplittingTokenizer__ Tokenizing base-class that will split on the given RegExp.
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Here are some example of how to import modules and classes:
__EnContactMatcher__ A domain specialization of using the `AcceleratedFuzzyMatcher` for English speakers searching over a list of names. Does additional preprocessing and setups up the distance function for you.
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__EnPlaceMatcher__ A domain specialization of using the `AcceleratedFuzzyMatcher` for English speakers searching over a list of places. Does additional preprocessing and setups up the distance function for you.
A .NET Core NuGet package is published for this project. The package is published by Microsoft. Hence, it must follow guidance at https://aka.ms/nuget and sign package content and package itself with an official Microsoft certificate. To ease signing and publishing process, we integrate ESRP signing to Azure DevOps build tasks.
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To publish a new version of the package, create a release for the latest build (Pipelines->Releases->PublishNuget->Create a release).
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# Contributors
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This project welcomes contributions and suggestions. Most contributions require you to
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agree to a Contributor License Agreement (CLA) declaring that you have the right to,
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