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# Language Identification Feature Extraction

The following schema describes the creation of language identification feature files that you can use to create and optimize language identification classifiers.

    [langIdFeature]
    0 = a <- audio(MONO, input)
    1 = f1   <- frontend1(_, a)
    2 = nf1  <- normalizer1(_, f1)
    3 = w <- audiopreproc(A, a, nf1)
    4 = f2 <- frontend2(_, a)
    5 = nf2 <- normalizer2(_, f2, w)
    6 = lf1 <- lidfeature(_, nf2)
    7 = lf2 <- filter(LF_INCLUSIVE, lf1, w)
    8 = output <- lfout(_, lf2)
    DefaultResults=out

`0` | The `audio` module processes the mono audio data.
`1` | The `frontend1` module converts the audio data from `0` into front-end frame data.
`2` | The `normalizer1` module normalizes the frame data from `1`.
`3` | The `audiopreproc1` module runs audio classification on the audio (`a`) and the normalized frame data from `2` (`nf1`).
`4` | The `frontend2` module converts the audio data from `0` into front-end frame data.
`5` | The `normalizer2` module normalizes the frame data from `4`.
`6` | The `lidfeature` module converts the normalized frame data from `5` (`nf2`) into language identification feature data.
`7` | The `filter` module filters the output from `6` (`lf1`), using the audio classification data (`w`), to include only language features that occur in segments that contain speech.
`8` | The `lfout` module writes the language identification feature data from `7` (`lf2`) to the output file.

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