Kaldi-based forced alignment
============================

This section describes in detail how to use `kaldi-decoder`_
for **FST-based** ``forced alignment`` with models trained by the `CTC`_ loss.

We will use the test data
from `CTC FORCED ALIGNMENT API TUTORIAL <https://pytorch.org/audio/main/tutorials/ctc_forced_alignment_api_tutorial.html>`_

Prepare the environment
-----------------------

Before you continue, make sure you have setup `icefall`_ by following :ref:`install icefall`.

.. hint::

   You don't need to install `Kaldi`_. We will ``NOT`` use `Kaldi`_ below.

Get the test data
-----------------

Compute log_probs
-----------------

Convert transcript to an FST graph
----------------------------------

Force aligner
-------------