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32 lines
757 B
ReStructuredText
32 lines
757 B
ReStructuredText
Kaldi-based forced alignment
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============================
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This section describes in detail how to use `kaldi-decoder`_
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for **FST-based** ``forced alignment`` with models trained by the `CTC`_ loss.
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We will use the test data
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from `CTC FORCED ALIGNMENT API TUTORIAL <https://pytorch.org/audio/main/tutorials/ctc_forced_alignment_api_tutorial.html>`_
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Prepare the environment
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-----------------------
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Before you continue, make sure you have setup `icefall`_ by following :ref:`install icefall`.
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.. hint::
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You don't need to install `Kaldi`_. We will ``NOT`` use `Kaldi`_ below.
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Get the test data
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-----------------
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Compute log_probs
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-----------------
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Convert transcript to an FST graph
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----------------------------------
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Force aligner
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-------------
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