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# Perform Speaker Identification Using Templates

The following schema describes how to run speaker identification given a set of templates.

    [ivSpkId]
    0 = a,ts <- audio(MONO, input)
    1 = w1 <- speakerid(GENDER_DETECT, a)
    2 = f1 <- frontend1(_,a)
    3 = nf1 <- normalizer1(_, f1)
    4 = w2 <- audiopreproc(A, a, nf1)
    5 = f2 <- frontend2(_,a)
    6 = nf2 <- normalizer2(SEGMENT_BLOCK, f2, w1)
    7 = nf3 <- filter(FEAT_INCLUSIVE, nf2, w2)
    8 = sid <- ivScore(SEGMENT, nf3, w1)
    9 = output <- sidout(_, sid, ts)

`0` | The `audio` module processes the mono audio data.
`1` | The `speakerid` module takes the audio data (`a`) and outputs speaker turn segments.
`2` | The `frontend1` module converts the audio data from `1` into front-end frame data.
`3` | The `normalizer1` module normalizes the frame data from `2`.
`4` | The `audiopreproc1` module in audio classification mode processes the audio (`a`) and normalized frame data (`nf1`).
`5` | The `frontend2` module converts the audio data from `0` into front-end frame data.
`6` | The `normalizer2` module normalizes the frame data from `5`.
`7` | The `filter` module filters the output from `6` (`nf2`) to include only frames that occur in segments that contain speech, by using the audio classification data from `4` (`w2`).
`4` | The `ivscore` module takes audio features from `7` (`nf3`) and speaker segment information (`w1`), and produces a set of iVector speaker scores for each segment.
`9` | The `sidout` module takes the speaker ID score information (`sid`) and writes this information into a results file.

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