.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/forced_alignment_tutorial.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_tutorials_forced_alignment_tutorial.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_tutorials_forced_alignment_tutorial.py:


Forced Alignment with Wav2Vec2
==============================

**Author**: `Moto Hira <moto@meta.com>`__

.. warning::
    Starting with version 2.8, we are refactoring TorchAudio to transition it
    into a maintenance phase. As a result:

    - The APIs described in this tutorial are deprecated in 2.8 and will be removed in 2.9.
    - The decoding and encoding capabilities of PyTorch for both audio and video
      are being consolidated into TorchCodec.

    Please see https://github.com/pytorch/audio/issues/3902 for more information.

This tutorial shows how to align transcript to speech with
``torchaudio``, using CTC segmentation algorithm described in
`CTC-Segmentation of Large Corpora for German End-to-end Speech
Recognition <https://arxiv.org/abs/2007.09127>`__.

.. note::

   This tutorial was originally written to illustrate a usecase
   for Wav2Vec2 pretrained model.

   TorchAudio now has a set of APIs designed for forced alignment.
   The `CTC forced alignment API tutorial
   <./ctc_forced_alignment_api_tutorial.html>`__ illustrates the
   usage of :py:func:`torchaudio.functional.forced_align`, which is
   the core API.

   If you are looking to align your corpus, we recommend to use
   :py:class:`torchaudio.pipelines.Wav2Vec2FABundle`, which combines
   :py:func:`~torchaudio.functional.forced_align` and other support
   functions with pre-trained model specifically trained for
   forced-alignment. Please refer to the
   `Forced alignment for multilingual data
   <forced_alignment_for_multilingual_data_tutorial.html>`__ which
   illustrates its usage.

.. GENERATED FROM PYTHON SOURCE LINES 42-54

.. code-block:: default


    import torch
    import torchaudio

    print(torch.__version__)
    print(torchaudio.__version__)


    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    print(device)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    2.8.0+cu126
    2.8.0
    cuda




.. GENERATED FROM PYTHON SOURCE LINES 55-68

Overview
--------

The process of alignment looks like the following.

1. Estimate the frame-wise label probability from audio waveform
2. Generate the trellis matrix which represents the probability of
   labels aligned at time step.
3. Find the most likely path from the trellis matrix.

In this example, we use ``torchaudio``\ ’s ``Wav2Vec2`` model for
acoustic feature extraction.


.. GENERATED FROM PYTHON SOURCE LINES 71-76

Preparation
-----------

First we import the necessary packages, and fetch data that we work on.


.. GENERATED FROM PYTHON SOURCE LINES 76-87

.. code-block:: default


    from dataclasses import dataclass

    import IPython
    import matplotlib.pyplot as plt

    torch.random.manual_seed(0)

    SPEECH_FILE = torchaudio.utils.download_asset("tutorial-assets/Lab41-SRI-VOiCES-src-sp0307-ch127535-sg0042.wav")






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    /pytorch/audio/examples/tutorials/forced_alignment_tutorial.py:84: UserWarning: torchaudio.utils.download.download_asset has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
      SPEECH_FILE = torchaudio.utils.download_asset("tutorial-assets/Lab41-SRI-VOiCES-src-sp0307-ch127535-sg0042.wav")




.. GENERATED FROM PYTHON SOURCE LINES 88-104

Generate frame-wise label probability
-------------------------------------

The first step is to generate the label class porbability of each audio
frame. We can use a Wav2Vec2 model that is trained for ASR. Here we use
:py:func:`torchaudio.pipelines.WAV2VEC2_ASR_BASE_960H`.

``torchaudio`` provides easy access to pretrained models with associated
labels.

.. note::

   In the subsequent sections, we will compute the probability in
   log-domain to avoid numerical instability. For this purpose, we
   normalize the ``emission`` with :py:func:`torch.log_softmax`.


.. GENERATED FROM PYTHON SOURCE LINES 104-117

.. code-block:: default


    bundle = torchaudio.pipelines.WAV2VEC2_ASR_BASE_960H
    model = bundle.get_model().to(device)
    labels = bundle.get_labels()
    with torch.inference_mode():
        waveform, _ = torchaudio.load(SPEECH_FILE)
        emissions, _ = model(waveform.to(device))
        emissions = torch.log_softmax(emissions, dim=-1)

    emission = emissions[0].cpu().detach()

    print(labels)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    /pytorch/audio/src/torchaudio/_backend/utils.py:213: UserWarning: In 2.9, this function's implementation will be changed to use torchaudio.load_with_torchcodec` under the hood. Some parameters like ``normalize``, ``format``, ``buffer_size``, and ``backend`` will be ignored. We recommend that you port your code to rely directly on TorchCodec's decoder instead: https://docs.pytorch.org/torchcodec/stable/generated/torchcodec.decoders.AudioDecoder.html#torchcodec.decoders.AudioDecoder.
      warnings.warn(
    /pytorch/audio/src/torchaudio/_backend/ffmpeg.py:88: UserWarning: torio.io._streaming_media_decoder.StreamingMediaDecoder has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release. 
      s = torchaudio.io.StreamReader(src, format, None, buffer_size)
    ('-', '|', 'E', 'T', 'A', 'O', 'N', 'I', 'H', 'S', 'R', 'D', 'L', 'U', 'M', 'W', 'C', 'F', 'G', 'Y', 'P', 'B', 'V', 'K', "'", 'X', 'J', 'Q', 'Z')




.. GENERATED FROM PYTHON SOURCE LINES 118-120

Visualization
~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 120-134

.. code-block:: default



    def plot():
        fig, ax = plt.subplots()
        img = ax.imshow(emission.T)
        ax.set_title("Frame-wise class probability")
        ax.set_xlabel("Time")
        ax.set_ylabel("Labels")
        fig.colorbar(img, ax=ax, shrink=0.6, location="bottom")
        fig.tight_layout()


    plot()




.. image-sg:: /tutorials/images/sphx_glr_forced_alignment_tutorial_001.png
   :alt: Frame-wise class probability
   :srcset: /tutorials/images/sphx_glr_forced_alignment_tutorial_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 135-171

Generate alignment probability (trellis)
----------------------------------------

From the emission matrix, next we generate the trellis which represents
the probability of transcript labels occur at each time frame.

Trellis is 2D matrix with time axis and label axis. The label axis
represents the transcript that we are aligning. In the following, we use
:math:`t` to denote the index in time axis and :math:`j` to denote the
index in label axis. :math:`c_j` represents the label at label index
:math:`j`.

To generate, the probability of time step :math:`t+1`, we look at the
trellis from time step :math:`t` and emission at time step :math:`t+1`.
There are two path to reach to time step :math:`t+1` with label
:math:`c_{j+1}`. The first one is the case where the label was
:math:`c_{j+1}` at :math:`t` and there was no label change from
:math:`t` to :math:`t+1`. The other case is where the label was
:math:`c_j` at :math:`t` and it transitioned to the next label
:math:`c_{j+1}` at :math:`t+1`.

The follwoing diagram illustrates this transition.

.. image:: https://download.pytorch.org/torchaudio/tutorial-assets/ctc-forward.png

Since we are looking for the most likely transitions, we take the more
likely path for the value of :math:`k_{(t+1, j+1)}`, that is

:math:`k_{(t+1, j+1)} = max( k_{(t, j)} p(t+1, c_{j+1}), k_{(t, j+1)} p(t+1, repeat) )`

where :math:`k` represents is trellis matrix, and :math:`p(t, c_j)`
represents the probability of label :math:`c_j` at time step :math:`t`.
:math:`repeat` represents the blank token from CTC formulation. (For the
detail of CTC algorithm, please refer to the *Sequence Modeling with CTC*
[`distill.pub <https://distill.pub/2017/ctc/>`__])


.. GENERATED FROM PYTHON SOURCE LINES 171-202

.. code-block:: default



    # We enclose the transcript with space tokens, which represent SOS and EOS.
    transcript = "|I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"
    dictionary = {c: i for i, c in enumerate(labels)}

    tokens = [dictionary[c] for c in transcript]
    print(list(zip(transcript, tokens)))


    def get_trellis(emission, tokens, blank_id=0):
        num_frame = emission.size(0)
        num_tokens = len(tokens)

        trellis = torch.zeros((num_frame, num_tokens))
        trellis[1:, 0] = torch.cumsum(emission[1:, blank_id], 0)
        trellis[0, 1:] = -float("inf")
        trellis[-num_tokens + 1 :, 0] = float("inf")

        for t in range(num_frame - 1):
            trellis[t + 1, 1:] = torch.maximum(
                # Score for staying at the same token
                trellis[t, 1:] + emission[t, blank_id],
                # Score for changing to the next token
                trellis[t, :-1] + emission[t, tokens[1:]],
            )
        return trellis


    trellis = get_trellis(emission, tokens)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [('|', 1), ('I', 7), ('|', 1), ('H', 8), ('A', 4), ('D', 11), ('|', 1), ('T', 3), ('H', 8), ('A', 4), ('T', 3), ('|', 1), ('C', 16), ('U', 13), ('R', 10), ('I', 7), ('O', 5), ('S', 9), ('I', 7), ('T', 3), ('Y', 19), ('|', 1), ('B', 21), ('E', 2), ('S', 9), ('I', 7), ('D', 11), ('E', 2), ('|', 1), ('M', 14), ('E', 2), ('|', 1), ('A', 4), ('T', 3), ('|', 1), ('T', 3), ('H', 8), ('I', 7), ('S', 9), ('|', 1), ('M', 14), ('O', 5), ('M', 14), ('E', 2), ('N', 6), ('T', 3), ('|', 1)]




.. GENERATED FROM PYTHON SOURCE LINES 203-205

Visualization
~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 205-218

.. code-block:: default



    def plot():
        fig, ax = plt.subplots()
        img = ax.imshow(trellis.T, origin="lower")
        ax.annotate("- Inf", (trellis.size(1) / 5, trellis.size(1) / 1.5))
        ax.annotate("+ Inf", (trellis.size(0) - trellis.size(1) / 5, trellis.size(1) / 3))
        fig.colorbar(img, ax=ax, shrink=0.6, location="bottom")
        fig.tight_layout()


    plot()




.. image-sg:: /tutorials/images/sphx_glr_forced_alignment_tutorial_002.png
   :alt: forced alignment tutorial
   :srcset: /tutorials/images/sphx_glr_forced_alignment_tutorial_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 219-222

In the above visualization, we can see that there is a trace of high
probability crossing the matrix diagonally.


.. GENERATED FROM PYTHON SOURCE LINES 225-244

Find the most likely path (backtracking)
----------------------------------------

Once the trellis is generated, we will traverse it following the
elements with high probability.

We will start from the last label index with the time step of highest
probability, then, we traverse back in time, picking stay
(:math:`c_j \rightarrow c_j`) or transition
(:math:`c_j \rightarrow c_{j+1}`), based on the post-transition
probability :math:`k_{t, j} p(t+1, c_{j+1})` or
:math:`k_{t, j+1} p(t+1, repeat)`.

Transition is done once the label reaches the beginning.

The trellis matrix is used for path-finding, but for the final
probability of each segment, we take the frame-wise probability from
emission matrix.


.. GENERATED FROM PYTHON SOURCE LINES 244-294

.. code-block:: default



    @dataclass
    class Point:
        token_index: int
        time_index: int
        score: float


    def backtrack(trellis, emission, tokens, blank_id=0):
        t, j = trellis.size(0) - 1, trellis.size(1) - 1

        path = [Point(j, t, emission[t, blank_id].exp().item())]
        while j > 0:
            # Should not happen but just in case
            assert t > 0

            # 1. Figure out if the current position was stay or change
            # Frame-wise score of stay vs change
            p_stay = emission[t - 1, blank_id]
            p_change = emission[t - 1, tokens[j]]

            # Context-aware score for stay vs change
            stayed = trellis[t - 1, j] + p_stay
            changed = trellis[t - 1, j - 1] + p_change

            # Update position
            t -= 1
            if changed > stayed:
                j -= 1

            # Store the path with frame-wise probability.
            prob = (p_change if changed > stayed else p_stay).exp().item()
            path.append(Point(j, t, prob))

        # Now j == 0, which means, it reached the SoS.
        # Fill up the rest for the sake of visualization
        while t > 0:
            prob = emission[t - 1, blank_id].exp().item()
            path.append(Point(j, t - 1, prob))
            t -= 1

        return path[::-1]


    path = backtrack(trellis, emission, tokens)
    for p in path:
        print(p)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Point(token_index=0, time_index=0, score=0.9999996423721313)
    Point(token_index=0, time_index=1, score=0.9999996423721313)
    Point(token_index=0, time_index=2, score=0.9999996423721313)
    Point(token_index=0, time_index=3, score=0.9999996423721313)
    Point(token_index=0, time_index=4, score=0.9999996423721313)
    Point(token_index=0, time_index=5, score=0.9999996423721313)
    Point(token_index=0, time_index=6, score=0.9999996423721313)
    Point(token_index=0, time_index=7, score=0.9999996423721313)
    Point(token_index=0, time_index=8, score=0.9999998807907104)
    Point(token_index=0, time_index=9, score=0.9999996423721313)
    Point(token_index=0, time_index=10, score=0.9999996423721313)
    Point(token_index=0, time_index=11, score=0.9999998807907104)
    Point(token_index=0, time_index=12, score=0.9999996423721313)
    Point(token_index=0, time_index=13, score=0.9999996423721313)
    Point(token_index=0, time_index=14, score=0.9999996423721313)
    Point(token_index=0, time_index=15, score=0.9999996423721313)
    Point(token_index=0, time_index=16, score=0.9999996423721313)
    Point(token_index=0, time_index=17, score=0.9999996423721313)
    Point(token_index=0, time_index=18, score=0.9999998807907104)
    Point(token_index=0, time_index=19, score=0.9999996423721313)
    Point(token_index=0, time_index=20, score=0.9999996423721313)
    Point(token_index=0, time_index=21, score=0.9999996423721313)
    Point(token_index=0, time_index=22, score=0.9999996423721313)
    Point(token_index=0, time_index=23, score=0.9999997615814209)
    Point(token_index=0, time_index=24, score=0.9999998807907104)
    Point(token_index=0, time_index=25, score=0.9999998807907104)
    Point(token_index=0, time_index=26, score=0.9999998807907104)
    Point(token_index=0, time_index=27, score=0.9999998807907104)
    Point(token_index=0, time_index=28, score=0.9999985694885254)
    Point(token_index=0, time_index=29, score=0.9999943971633911)
    Point(token_index=0, time_index=30, score=0.9999842643737793)
    Point(token_index=1, time_index=31, score=0.9846633672714233)
    Point(token_index=1, time_index=32, score=0.9999706745147705)
    Point(token_index=1, time_index=33, score=0.15361329913139343)
    Point(token_index=1, time_index=34, score=0.9999172687530518)
    Point(token_index=2, time_index=35, score=0.6085338592529297)
    Point(token_index=2, time_index=36, score=0.9997722506523132)
    Point(token_index=3, time_index=37, score=0.999714195728302)
    Point(token_index=3, time_index=38, score=0.9999358654022217)
    Point(token_index=4, time_index=39, score=0.9861765503883362)
    Point(token_index=4, time_index=40, score=0.9241003394126892)
    Point(token_index=5, time_index=41, score=0.9259175062179565)
    Point(token_index=5, time_index=42, score=0.015625856816768646)
    Point(token_index=5, time_index=43, score=0.9998376369476318)
    Point(token_index=6, time_index=44, score=0.9988446235656738)
    Point(token_index=7, time_index=45, score=0.10159187018871307)
    Point(token_index=7, time_index=46, score=0.9999426603317261)
    Point(token_index=8, time_index=47, score=0.9999943971633911)
    Point(token_index=8, time_index=48, score=0.9979596138000488)
    Point(token_index=9, time_index=49, score=0.036005258560180664)
    Point(token_index=9, time_index=50, score=0.06174848601222038)
    Point(token_index=9, time_index=51, score=4.3377182009862736e-05)
    Point(token_index=10, time_index=52, score=0.9999799728393555)
    Point(token_index=11, time_index=53, score=0.9967069029808044)
    Point(token_index=11, time_index=54, score=0.9999257326126099)
    Point(token_index=11, time_index=55, score=0.9999982118606567)
    Point(token_index=12, time_index=56, score=0.999064028263092)
    Point(token_index=12, time_index=57, score=0.9999996423721313)
    Point(token_index=12, time_index=58, score=0.9999996423721313)
    Point(token_index=12, time_index=59, score=0.8450244069099426)
    Point(token_index=12, time_index=60, score=0.9999996423721313)
    Point(token_index=13, time_index=61, score=0.9996004700660706)
    Point(token_index=13, time_index=62, score=0.999998927116394)
    Point(token_index=14, time_index=63, score=0.003534560324624181)
    Point(token_index=14, time_index=64, score=1.0)
    Point(token_index=14, time_index=65, score=1.0)
    Point(token_index=14, time_index=66, score=0.9999915361404419)
    Point(token_index=15, time_index=67, score=0.9971501231193542)
    Point(token_index=15, time_index=68, score=0.9999990463256836)
    Point(token_index=15, time_index=69, score=0.9999992847442627)
    Point(token_index=15, time_index=70, score=0.9999997615814209)
    Point(token_index=15, time_index=71, score=0.9999998807907104)
    Point(token_index=15, time_index=72, score=0.9999880790710449)
    Point(token_index=15, time_index=73, score=0.011419214308261871)
    Point(token_index=15, time_index=74, score=0.9999977350234985)
    Point(token_index=16, time_index=75, score=0.9996128678321838)
    Point(token_index=16, time_index=76, score=0.999998927116394)
    Point(token_index=16, time_index=77, score=0.9729052782058716)
    Point(token_index=16, time_index=78, score=0.999998927116394)
    Point(token_index=17, time_index=79, score=0.9949370622634888)
    Point(token_index=17, time_index=80, score=0.999998927116394)
    Point(token_index=17, time_index=81, score=0.9999125003814697)
    Point(token_index=17, time_index=82, score=0.9999774694442749)
    Point(token_index=18, time_index=83, score=0.6575068831443787)
    Point(token_index=18, time_index=84, score=0.9984293580055237)
    Point(token_index=18, time_index=85, score=0.9999876022338867)
    Point(token_index=19, time_index=86, score=0.9993751645088196)
    Point(token_index=19, time_index=87, score=0.9999988079071045)
    Point(token_index=19, time_index=88, score=0.10444644093513489)
    Point(token_index=19, time_index=89, score=0.9999969005584717)
    Point(token_index=20, time_index=90, score=0.3971569836139679)
    Point(token_index=20, time_index=91, score=0.9999932050704956)
    Point(token_index=21, time_index=92, score=1.696418848950998e-06)
    Point(token_index=21, time_index=93, score=0.9860828518867493)
    Point(token_index=21, time_index=94, score=0.9999960660934448)
    Point(token_index=22, time_index=95, score=0.9992727637290955)
    Point(token_index=22, time_index=96, score=0.9993411898612976)
    Point(token_index=22, time_index=97, score=0.9999983310699463)
    Point(token_index=23, time_index=98, score=0.9999971389770508)
    Point(token_index=23, time_index=99, score=0.9999998807907104)
    Point(token_index=23, time_index=100, score=0.9999995231628418)
    Point(token_index=23, time_index=101, score=0.9999732971191406)
    Point(token_index=24, time_index=102, score=0.9983185529708862)
    Point(token_index=24, time_index=103, score=0.9999991655349731)
    Point(token_index=24, time_index=104, score=0.9999996423721313)
    Point(token_index=24, time_index=105, score=0.9999998807907104)
    Point(token_index=24, time_index=106, score=1.0)
    Point(token_index=24, time_index=107, score=0.999862551689148)
    Point(token_index=24, time_index=108, score=0.9999980926513672)
    Point(token_index=25, time_index=109, score=0.9988523721694946)
    Point(token_index=25, time_index=110, score=0.9999798536300659)
    Point(token_index=26, time_index=111, score=0.8575892448425293)
    Point(token_index=26, time_index=112, score=0.9999847412109375)
    Point(token_index=27, time_index=113, score=0.9870195388793945)
    Point(token_index=27, time_index=114, score=1.9013934434042312e-05)
    Point(token_index=27, time_index=115, score=0.9999796152114868)
    Point(token_index=28, time_index=116, score=0.9998248219490051)
    Point(token_index=28, time_index=117, score=0.9999990463256836)
    Point(token_index=29, time_index=118, score=0.9999732971191406)
    Point(token_index=29, time_index=119, score=0.0008990301284939051)
    Point(token_index=29, time_index=120, score=0.9993460774421692)
    Point(token_index=30, time_index=121, score=0.9975366592407227)
    Point(token_index=30, time_index=122, score=0.000303806911688298)
    Point(token_index=30, time_index=123, score=0.9999344348907471)
    Point(token_index=31, time_index=124, score=6.088280770200072e-06)
    Point(token_index=31, time_index=125, score=0.9833387136459351)
    Point(token_index=32, time_index=126, score=0.9974588751792908)
    Point(token_index=33, time_index=127, score=0.0008261289913207293)
    Point(token_index=33, time_index=128, score=0.9965143799781799)
    Point(token_index=34, time_index=129, score=0.017432427033782005)
    Point(token_index=34, time_index=130, score=0.9989168643951416)
    Point(token_index=35, time_index=131, score=0.9999697208404541)
    Point(token_index=36, time_index=132, score=0.9999842643737793)
    Point(token_index=36, time_index=133, score=0.9997639060020447)
    Point(token_index=37, time_index=134, score=0.5108126401901245)
    Point(token_index=37, time_index=135, score=0.9998301267623901)
    Point(token_index=38, time_index=136, score=0.08521389961242676)
    Point(token_index=38, time_index=137, score=0.004068504087626934)
    Point(token_index=38, time_index=138, score=0.9999815225601196)
    Point(token_index=39, time_index=139, score=0.011991607956588268)
    Point(token_index=39, time_index=140, score=0.9999980926513672)
    Point(token_index=39, time_index=141, score=0.0005900734104216099)
    Point(token_index=39, time_index=142, score=0.9999085664749146)
    Point(token_index=40, time_index=143, score=0.9999960660934448)
    Point(token_index=40, time_index=144, score=0.9999980926513672)
    Point(token_index=40, time_index=145, score=0.9999916553497314)
    Point(token_index=41, time_index=146, score=0.9971139430999756)
    Point(token_index=41, time_index=147, score=0.9981796741485596)
    Point(token_index=41, time_index=148, score=0.9999310970306396)
    Point(token_index=42, time_index=149, score=0.9879123568534851)
    Point(token_index=42, time_index=150, score=0.9997639060020447)
    Point(token_index=42, time_index=151, score=0.9999536275863647)
    Point(token_index=43, time_index=152, score=0.9999715089797974)
    Point(token_index=44, time_index=153, score=0.32006949186325073)
    Point(token_index=44, time_index=154, score=0.9997830986976624)
    Point(token_index=45, time_index=155, score=0.01606338657438755)
    Point(token_index=45, time_index=156, score=0.999901294708252)
    Point(token_index=46, time_index=157, score=0.46633121371269226)
    Point(token_index=46, time_index=158, score=0.9999994039535522)
    Point(token_index=46, time_index=159, score=0.9999996423721313)
    Point(token_index=46, time_index=160, score=0.9999995231628418)
    Point(token_index=46, time_index=161, score=0.9999996423721313)
    Point(token_index=46, time_index=162, score=0.9999996423721313)
    Point(token_index=46, time_index=163, score=0.9999996423721313)
    Point(token_index=46, time_index=164, score=0.9999995231628418)
    Point(token_index=46, time_index=165, score=0.9999995231628418)
    Point(token_index=46, time_index=166, score=0.9999996423721313)
    Point(token_index=46, time_index=167, score=0.9999996423721313)
    Point(token_index=46, time_index=168, score=0.9999995231628418)




.. GENERATED FROM PYTHON SOURCE LINES 295-297

Visualization
~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 297-311

.. code-block:: default



    def plot_trellis_with_path(trellis, path):
        # To plot trellis with path, we take advantage of 'nan' value
        trellis_with_path = trellis.clone()
        for _, p in enumerate(path):
            trellis_with_path[p.time_index, p.token_index] = float("nan")
        plt.imshow(trellis_with_path.T, origin="lower")
        plt.title("The path found by backtracking")
        plt.tight_layout()


    plot_trellis_with_path(trellis, path)




.. image-sg:: /tutorials/images/sphx_glr_forced_alignment_tutorial_003.png
   :alt: The path found by backtracking
   :srcset: /tutorials/images/sphx_glr_forced_alignment_tutorial_003.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 312-313

Looking good.

.. GENERATED FROM PYTHON SOURCE LINES 315-323

Segment the path
----------------
Now this path contains repetations for the same labels, so
let’s merge them to make it close to the original transcript.

When merging the multiple path points, we simply take the average
probability for the merged segments.


.. GENERATED FROM PYTHON SOURCE LINES 323-365

.. code-block:: default



    # Merge the labels
    @dataclass
    class Segment:
        label: str
        start: int
        end: int
        score: float

        def __repr__(self):
            return f"{self.label}\t({self.score:4.2f}): [{self.start:5d}, {self.end:5d})"

        @property
        def length(self):
            return self.end - self.start


    def merge_repeats(path):
        i1, i2 = 0, 0
        segments = []
        while i1 < len(path):
            while i2 < len(path) and path[i1].token_index == path[i2].token_index:
                i2 += 1
            score = sum(path[k].score for k in range(i1, i2)) / (i2 - i1)
            segments.append(
                Segment(
                    transcript[path[i1].token_index],
                    path[i1].time_index,
                    path[i2 - 1].time_index + 1,
                    score,
                )
            )
            i1 = i2
        return segments


    segments = merge_repeats(path)
    for seg in segments:
        print(seg)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    |       (1.00): [    0,    31)
    I       (0.78): [   31,    35)
    |       (0.80): [   35,    37)
    H       (1.00): [   37,    39)
    A       (0.96): [   39,    41)
    D       (0.65): [   41,    44)
    |       (1.00): [   44,    45)
    T       (0.55): [   45,    47)
    H       (1.00): [   47,    49)
    A       (0.03): [   49,    52)
    T       (1.00): [   52,    53)
    |       (1.00): [   53,    56)
    C       (0.97): [   56,    61)
    U       (1.00): [   61,    63)
    R       (0.75): [   63,    67)
    I       (0.88): [   67,    75)
    O       (0.99): [   75,    79)
    S       (1.00): [   79,    83)
    I       (0.89): [   83,    86)
    T       (0.78): [   86,    90)
    Y       (0.70): [   90,    92)
    |       (0.66): [   92,    95)
    B       (1.00): [   95,    98)
    E       (1.00): [   98,   102)
    S       (1.00): [  102,   109)
    I       (1.00): [  109,   111)
    D       (0.93): [  111,   113)
    E       (0.66): [  113,   116)
    |       (1.00): [  116,   118)
    M       (0.67): [  118,   121)
    E       (0.67): [  121,   124)
    |       (0.49): [  124,   126)
    A       (1.00): [  126,   127)
    T       (0.50): [  127,   129)
    |       (0.51): [  129,   131)
    T       (1.00): [  131,   132)
    H       (1.00): [  132,   134)
    I       (0.76): [  134,   136)
    S       (0.36): [  136,   139)
    |       (0.50): [  139,   143)
    M       (1.00): [  143,   146)
    O       (1.00): [  146,   149)
    M       (1.00): [  149,   152)
    E       (1.00): [  152,   153)
    N       (0.66): [  153,   155)
    T       (0.51): [  155,   157)
    |       (0.96): [  157,   169)




.. GENERATED FROM PYTHON SOURCE LINES 366-368

Visualization
~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 368-413

.. code-block:: default



    def plot_trellis_with_segments(trellis, segments, transcript):
        # To plot trellis with path, we take advantage of 'nan' value
        trellis_with_path = trellis.clone()
        for i, seg in enumerate(segments):
            if seg.label != "|":
                trellis_with_path[seg.start : seg.end, i] = float("nan")

        fig, [ax1, ax2] = plt.subplots(2, 1, sharex=True)
        ax1.set_title("Path, label and probability for each label")
        ax1.imshow(trellis_with_path.T, origin="lower", aspect="auto")

        for i, seg in enumerate(segments):
            if seg.label != "|":
                ax1.annotate(seg.label, (seg.start, i - 0.7), size="small")
                ax1.annotate(f"{seg.score:.2f}", (seg.start, i + 3), size="small")

        ax2.set_title("Label probability with and without repetation")
        xs, hs, ws = [], [], []
        for seg in segments:
            if seg.label != "|":
                xs.append((seg.end + seg.start) / 2 + 0.4)
                hs.append(seg.score)
                ws.append(seg.end - seg.start)
                ax2.annotate(seg.label, (seg.start + 0.8, -0.07))
        ax2.bar(xs, hs, width=ws, color="gray", alpha=0.5, edgecolor="black")

        xs, hs = [], []
        for p in path:
            label = transcript[p.token_index]
            if label != "|":
                xs.append(p.time_index + 1)
                hs.append(p.score)

        ax2.bar(xs, hs, width=0.5, alpha=0.5)
        ax2.axhline(0, color="black")
        ax2.grid(True, axis="y")
        ax2.set_ylim(-0.1, 1.1)
        fig.tight_layout()


    plot_trellis_with_segments(trellis, segments, transcript)





.. image-sg:: /tutorials/images/sphx_glr_forced_alignment_tutorial_004.png
   :alt: Path, label and probability for each label, Label probability with and without repetation
   :srcset: /tutorials/images/sphx_glr_forced_alignment_tutorial_004.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 414-415

Looks good.

.. GENERATED FROM PYTHON SOURCE LINES 417-426

Merge the segments into words
-----------------------------
Now let’s merge the words. The Wav2Vec2 model uses ``'|'``
as the word boundary, so we merge the segments before each occurance of
``'|'``.

Then, finally, we segment the original audio into segmented audio and
listen to them to see if the segmentation is correct.


.. GENERATED FROM PYTHON SOURCE LINES 426-450

.. code-block:: default


    # Merge words
    def merge_words(segments, separator="|"):
        words = []
        i1, i2 = 0, 0
        while i1 < len(segments):
            if i2 >= len(segments) or segments[i2].label == separator:
                if i1 != i2:
                    segs = segments[i1:i2]
                    word = "".join([seg.label for seg in segs])
                    score = sum(seg.score * seg.length for seg in segs) / sum(seg.length for seg in segs)
                    words.append(Segment(word, segments[i1].start, segments[i2 - 1].end, score))
                i1 = i2 + 1
                i2 = i1
            else:
                i2 += 1
        return words


    word_segments = merge_words(segments)
    for word in word_segments:
        print(word)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    I       (0.78): [   31,    35)
    HAD     (0.84): [   37,    44)
    THAT    (0.52): [   45,    53)
    CURIOSITY       (0.89): [   56,    92)
    BESIDE  (0.94): [   95,   116)
    ME      (0.67): [  118,   124)
    AT      (0.66): [  126,   129)
    THIS    (0.70): [  131,   139)
    MOMENT  (0.88): [  143,   157)




.. GENERATED FROM PYTHON SOURCE LINES 451-453

Visualization
~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 453-499

.. code-block:: default

    def plot_alignments(trellis, segments, word_segments, waveform, sample_rate=bundle.sample_rate):
        trellis_with_path = trellis.clone()
        for i, seg in enumerate(segments):
            if seg.label != "|":
                trellis_with_path[seg.start : seg.end, i] = float("nan")

        fig, [ax1, ax2] = plt.subplots(2, 1)

        ax1.imshow(trellis_with_path.T, origin="lower", aspect="auto")
        ax1.set_facecolor("lightgray")
        ax1.set_xticks([])
        ax1.set_yticks([])

        for word in word_segments:
            ax1.axvspan(word.start - 0.5, word.end - 0.5, edgecolor="white", facecolor="none")

        for i, seg in enumerate(segments):
            if seg.label != "|":
                ax1.annotate(seg.label, (seg.start, i - 0.7), size="small")
                ax1.annotate(f"{seg.score:.2f}", (seg.start, i + 3), size="small")

        # The original waveform
        ratio = waveform.size(0) / sample_rate / trellis.size(0)
        ax2.specgram(waveform, Fs=sample_rate)
        for word in word_segments:
            x0 = ratio * word.start
            x1 = ratio * word.end
            ax2.axvspan(x0, x1, facecolor="none", edgecolor="white", hatch="/")
            ax2.annotate(f"{word.score:.2f}", (x0, sample_rate * 0.51), annotation_clip=False)

        for seg in segments:
            if seg.label != "|":
                ax2.annotate(seg.label, (seg.start * ratio, sample_rate * 0.55), annotation_clip=False)
        ax2.set_xlabel("time [second]")
        ax2.set_yticks([])
        fig.tight_layout()


    plot_alignments(
        trellis,
        segments,
        word_segments,
        waveform[0],
    )





.. image-sg:: /tutorials/images/sphx_glr_forced_alignment_tutorial_005.png
   :alt: forced alignment tutorial
   :srcset: /tutorials/images/sphx_glr_forced_alignment_tutorial_005.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 500-503

Audio Samples
-------------


.. GENERATED FROM PYTHON SOURCE LINES 503-515

.. code-block:: default



    def display_segment(i):
        ratio = waveform.size(1) / trellis.size(0)
        word = word_segments[i]
        x0 = int(ratio * word.start)
        x1 = int(ratio * word.end)
        print(f"{word.label} ({word.score:.2f}): {x0 / bundle.sample_rate:.3f} - {x1 / bundle.sample_rate:.3f} sec")
        segment = waveform[:, x0:x1]
        return IPython.display.Audio(segment.numpy(), rate=bundle.sample_rate)









.. GENERATED FROM PYTHON SOURCE LINES 517-523

.. code-block:: default


    # Generate the audio for each segment
    print(transcript)
    IPython.display.Audio(SPEECH_FILE)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    |I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/x-wav;base64,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" type="audio/x-wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 525-528

.. code-block:: default


    display_segment(0)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    I (0.78): 0.624 - 0.704 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 530-533

.. code-block:: default


    display_segment(1)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    HAD (0.84): 0.744 - 0.885 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 535-538

.. code-block:: default


    display_segment(2)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    THAT (0.52): 0.905 - 1.066 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,UklGRkIUAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0YR4UAAA6KgksAy3sKHYfDRWtC60BjP16/Ur/5wKA/gn58vJP8crwjesp60bvq/Ol8ffwv+ql2/LOh8DQt2OwFa8yuOvGT86i48zpbuZS3OrXDOid+uYLUx25L/c7MjDmHz8TiQqZAIoDtQ5/GV0NVQA082vjR9PDxz/MzdSg4BjpPe8U8IjnIeFP5vLzMQPIEyMlujKaNJct6iS0GbcV4hTJG/4fvR3iE2AD0fHP4VHWk9HE1X3c3uTL6nbtN+7Z7mT2FgqdHGYztUQTTU1VS1T6TMRCwzlENvw0/TFKKV8chAsm+PbqQ+Nh4JrixOYa7dD09vYP9uT1b/hz/lMHZRMyGvsdYx2hGCYQvQas+o31CvHf6ZLb3ctqtcmkFI4BgLSJbJl1qdvAVOIy9Lbxy+Il6rgJvyxWRrpZTGhRZ7VX5kHCMUYfOA4kDmMYOxWM/L/fT8dTtyyr/qgvsGW9+c1a3AXpR+2k60jvYgDSG4gynUO+TZZRQksAQBsvgh8bFVcRDBHvCkT/suoM1PXCRbjcszG2SL6+ybTXi+N26wfvVfTZ/0YTrDAQT45heGdeaPJf+1L2QZM2aC4iKUgiOBfKBQXxj9tszbzLwNFo3BPpX/gPBAgKag0lEYcXGSOAM7I9OUPpPPMwWSTaG9gQegPn/db9r/kv8o7jRc5RvtexFK2opxeYOpKZkqCYXa7bwNrU4QMLEGoZ7A8yFR4sU0inVT5j8FryU9I/VChBED/37eFb1s/Z/dz2ypO6WKmcobKjgLBSwefYFPJRCy4eNCi4KssqIjEePm9LRU5qTRRCWClcEhH5uOWY1qTPN87ty0HJer+ttImwjbT4v7LSWOZD+WcK1BgJJEsoFSgoK/QyMDntQhtH7EIAOQwswRuBEIsIJwXTBNYEGwWcAsT/VfzG+9f/jwjVEIkWcR3fI7cmfyZfJWojvSTDJu8q6iluIgIXlwswAaj6Dveh9b32FfTA8e3wWOps5XDd/dzK3iLgouDh4ovdPtn+ywnG5rngsKe15MWy4YYJpBiaEzT9xfSt/9oaninWN1o5pD1ZNZQmHA+P+2vlFeMf6zn7nfR26OjW38zLyL7OGdXT4ujyhgXFEswZ/BVxC/EEbwpBFPMdKSE5ICkWqwhx+broCtv71XHXjd0I5D/kdd+p2k7ZFt+l5yr1xABNDG0ZhCKNJRYj/h01HMga/R6yIcgdhhg9ET8KwgTL/5v/4QHuBI8O6xJMFZcTZhEtE7cVXhcRGdEZ+hsnG0MX6hP1DjEL2gniCkQNMg69DdkL0glsCE0FqgIxAfr+Iv6w+xf7ZfiC87vxKO+08PTz4PY898Lye+1I6zbnvegW5xzhWtxV023H9rZSpvKrGssx9x8kqxtBCKPxLwNxHBIr+SqqMtM3ND6ZKQUXSPnn2K3Auckt4ILpxNdFy0TC68XFwy3Nldt67t7/fxI+JJ4sCyNhGDsXPiHgJw8pqSVlG8IHY/Qx4KzUdMr8xcrJodcm5Jjmt+AB3wHmi/L+AYQTqiF5LqU1yzf1Mbsm8xhND2kLZAhoAzb7fu854L7QYcj3yu/R7tt15wT5HgpCFrwZSB8xJU8teDP9OV1Ca0JNOk8srh0HE0kJhALxAT//S/6P+3n5Cfkx+Lj4jf1JA0kNzRPtFv8XbBT/EDcPQQuLCp4HjAZNBLT+Cv1S+aDzH/Ic663nxuTn3d3XZtEQzDTCE7vrq46dTJS8uJAK7jVrMXkMT/0uD8sXVBtrLnU+NENYLk8ihx4C+GjCbalUuefXsuCX4sHcMNZOx2m+xMs85gz5igYpII07a0GGMBwd7g6yB3MFQQ2iFw4SvPxv3bjN0cREuCqynbh9y1Pesei17q7t6ush7P3zdwY8HIsoLC5mMCIwrSaoF+IJbP+v+Yj6SwEsAvP3Muam2h7bMd1y37zpFf30DwQdtiVYK5coeCCLHtgnCje8P6U8ajQBLEwhtxHBCJ4DgQK8AAYCJwT+Aa37FvXz76rypfkyAFwGpgcABrwCLgGA/j/52/aK+Ij9AACMAlACwP+4+hL5gvgO/Q3/y/st99nz0u3i6LvfhdpW1yzV+M/dyYa8fK/JrKPGexOAQLk46Qj17TX7GxBUG4YuVTqQNzgdIAjaBV7x7MUlqEGzedKn4YThSdur0V3EKLzbzCnrswPaBdQMyRxWJG0bvQ17AML8vABXD88eExzxBCTjuM9OzZHNQtLK1zrhxOmv8N/1I/Yw8+TxXvf5CTAj3jVuOmszgyfiHnIZhhZPFOgQOgzHCtMIzv9l8ADgz9gn2gfh4eyH+WYC7wXOBmwNdxJtFEATlRV5H+wqLC5VKZYdjBH0BA4BxAOpB74GHQQ6AjgB0/6B+/33BPl5/nEG7xE7F/gVYhLLDkUOrQ3TDkMNowtYCdEIrAe5An/5Y/Aq7c/v5fX0+sb4DvMY7hbsxO4i8Zjx3u5R6ZjkSuFU3cjSFMPsumy9ccwE66QRZhcw/bvbgtpV7wkFng+KGeQetBkHCe3/ZvuI5/XNKMdI22v0Gf3P9eXkSNfKzaLRWOXT/UwKNw5hE58X8RegEtENLAh8B4kLKxfuHv0YtwUY8ejjjd+Y5Gbt3fKb9Vz1v/Qd9Pb0SfNV9OP2tQJ2EVwenSGuG1kS8wkwBpMIXA1XD1wNTwpGBP775PMq7xbsauu77lL4AAPACL8HjQVfBu4Jow9fGX4iUSjiKRAqsijLJJUesBfHEY4R8hHhEKwKtgHQ+Yr0wPNF9Wv3ePiE+br7tvw1/rb9SP5V/70B2AbCDHkLDgbC/gT7j/mu+D74u/Yo9AHwV+uH6anoTeid5xbpFOgv6xrsRuzI6p3qVOfT4kHgS97h2yvYs9g27kMaTi3WFKLsReQ08yABDg+xHkEoaBar/J30xPlR8RPfpduu6xT8QQRwAhj2NuI10CTQMuQU/NAJkguGBzgBDv+aAiIEbQEAA1UOqBzuJPAglxJk/R7wXfJ3/wcL6g76DXkHqfxg9VP3f/lQ+Qf7egNwDu0UQBM6DFoDTP8PBYwRWB0BIl8hzhzSFFENeAqNCJ0GvwT5BPMG1QfuAhX5v++g7OftkfD99MH6K/8eAC7/lwGBBBQHhQs3FvIdiyDAHCQYYxH+DC4NBg/GDb0JHgWkADn9W/nJ9XjzafKG9CX4aPq7+/n5Rvsu+tz/XQXQCa4Iogc1BZwEKwSBBFYEKgJ4/2j/uP+N/eP4dPPW8Ijycfkq/qb8yvZ077rqH+r767XtaO0j7G3tru136g3j1NoH0iTV9PqtHxghLPrs4l3rJft6BiUXcyujIF0K5QVnFK4Mpvq6+bsBlwHwAPwQ5hOV/VnnfOpm9uz4OwSiElkQv/sd+ZkFsAlcA/cGFg+oDSYPtBuvH3gNWf9UA3cLEA0uFD0fXhibBhcAjweICC4FkQfZCn4F0QHuBpsIkv9999P4wf2EAW4GRQouCGgCXP8O/yoCbwYyCTMGPQK0AgEEXgGi/n7+mfxF+Tb6Dv/3ALr+tftb+fH20PYg+4f+ef0J/BH+wQAO/5H+JP8k/i/80f0OA9gGYwcDBi0EgwPTBIcGTgYMBb8EIAaQBvIHcwllCjsIlwTiAp0EYwcEB6MFcwSaA4EEDQZRBBUBAwHzAYsC4QEIBBUHDwSU/s8CKATo/nj8uwHGAYz+wP/9AhX+kvgg+X77sfxd/4ECkgMDAJz8//rO+vP9tgAwAf4C5gS3AocC1AKb/7f7Bv51AZUDqwWMB9oFhAFV/w7/RABgA/kGewpyCsoJuQfxBvwGzAj5CPUI/Qr2DIcNFgzECukIQgdUBrsG/AYVCGkH+gPGAEb+2/1y/18AVP83/n/9gf54/y3+Nv1q/XH9Zv0qAEMEqAR9ACL+u/9QAigExQQbBfUD2QH9AMsB9wHy/zf8ZPv6/aj///y9+Wf4C/gu+CP6qv0ZAWYCqwGNAWgCYAJ1ASQCXwWXB8IHsgY5BX0DkAEPAPr/KQEtAlICwgJdAzoCgwB+AN4B3wKDA/4EdAbNBpAFyAS4BJEEKQX+BqkISgjmBoEF8QQGBQsF3gSkBHAF6AaRB8AGDwWKA/oDWgU4B8wIbQglB60GTAjQCeIJFwpEC4ULBwtXCogKbwpJCUIIiwhdCIsH1gYJB/sGrgbtBdsE1QQaBpIGHwV7A2gC2wGHAvQDzAXGBgsGEARpBMsG5QdIB+oFvAW+BeAGiwjICaUI1AWKBO4EuwVMBV4EXQJlABMAwgAzAaP/Xv4Z/lL/gQC7AboB4gBv/0n/TgGxApcCjwGpAM7/C//2/qr+o/0G/Wb9Tv2v/Hn8E/2u/SL+jv9AARMDSwSkBDYERgRoBdMGKge/B8EItAnRCBoHMQXtA+UCRgO3BKYFHwW4A7sB1/+q/gwAiwKDAwkDtALdAr8CNQKmAkQDyQM6BS0HJAjXBw4HGAbvBRYGjQaiBh0GAgZOBtIFFwRsAcH/i/5d/sP/oAEtAm8BmwA6AAQAMgCRAFwBQALgAmoD7QLUAQAAIf++/0IAMQHWAWwBWwD1/yYA8gBDARUBOQBw/+r/OgAEAIr/IP+R/kP+Bv86AIYAL//f/uT/IwEsAoACtQIQA4MD9wPXAzcDYAK+AO//s/81AH4A0//N/hL+Rv4n/0UAfAHZAQQCnAL+AmIDiwO5AyoEnwTxBEAEagM6AqMAWv+s/nv/SgCrAIsAWgCBAEoAof/4/gD/5v/7AFUCLANZAzwDuQJTAksCeALzAmcDDQR/BJoErAQ4BHsDhAJxAsUC5wLzAjcD9APNBO4EgQQlBNoEuwWNBowHFQmuCokLYwt4CnQJkgjlBwAINwjXB4MHUwdLBrsELgM9AnEBKAG+Ab0CgAPDAw4D6wHzAFcBVgK0AhwCdQEGAEH/Gv5B/cH8J/wY++/6sPv//Pj87PuG+4/7vfub/Ln9z/71/gH/4f9AARwCRwEAAMYAHAJUBH8IpAdeAf3+rf/q/8YAsQLlAqUBOAEnArsBBQG7AbcC2gK0A9gEyARDBFUDhQNRA6sA7v04/gwANAGEAnADBgMGAtkAtgB2ADYBtQHIATABHgFVAp8C/wFpAdYBBgJOAuACaQK+ARYBMQFEAbsBNQIdAm8BUwDG/9EAEAE8ANz/rgAdAd8AAAGjANf/UgDiAKUBiwIXBZMFnwQzA2sCjQNtAzsCPQIqAsoCJQLRASgBQgB4/0T/TP9i/wwAiQDnAJABSAIAA80CMAKHAmoDsQOVA6kDQQT/A7ED2wL3AVQBdgC7/8/+Tv43/k//eP8+/1n/BwBNAC0AsQCxAHAAUwCvADEBdAHDAVQBIAEBAJv/g//E/zP/Mv5z/nv/eP8p/wv/EP9U/zz/6v9XAZ8BQAG5ADABIAJzAgcCYQFqAVgCTwNsA6ADnQMxA5MCvwKHA+EDngNyAxQEkQSaBP4ERQXYBGwE2ASLBaQFFAW4BB8F1QXPBUwF/gRmBB0EegSPBCoFLwVXBdsEHwW3BXIFrAQ2BIEEWAS0BBEFLwXjBCoEvgPEA0gEcQSaBIwEtQSvBGkE/wMbAx4DWQPnAxQECAT6A6gD/gLSApsDTgTYBM4ELwU1BQcF8QQxBWcFJgX8BPME7QSOBOQDeAPSAqYC8wGEAUQBdAFkARsBCAHcADoApf9k/9z/JgBFAIkAtwCIALP/K/9N/4X/mP+A/9z/MQAyAOL/RQChAHMASgB9ABsBjQHvAVICJAK2ASsBLgFDAboBXQJWAkoCfAK0AlMCrQFnAWoB1gFeAsAC+ALHAnMCLQIfAiAC1AE0Af8AXwGqAU8BkwBlAIgACwF6AcsBxgGSAVEB8wHEAhQD6gJ7AjgCWwLPAv4CjgKNASMBTwFpATQBkQD6/2r/uf9+AOwA1wBtAD8AZQDNALMBYwI6A6kDDASwA0kDIwPiAhkCaQHbAXEC4wGvAAAAtP8G//v+Bf/L/8n/s/+z/6X/Of8F/5P/MgDZADEB0wH8AaIBDQGnAH0AtAAFAewATAAmAGYAfgBfAFcARQBSAJQAkAFoAocCIgLWAWACwAL7Av4CLwPyAroC5QJCA8QCqgG5AIwA8gArAfoAiAD9/4r/kv8aAPgAIwEAAeIA8gBPAYwBggGEAZcB5wFwAu0C1AJYAsgBYgEtAWEBmAHjAdsB0wGPAUMBDgHdAKEAmABAAV0CNAMAA2MCRQKxAs8C/QJtA3gDCwN7AhcC2AFPAd8AkACxANcAHgEeAfcAIQGNAeABhgIvA5UDkAN0A7sDvgN1AzkD9gKxAjAC4wFeAYAAsf9E/4P/nf+Y/2L/Df+T/hf+IP6P/j//xv8/ADkADgCd/y//Fv8Q//7+8/71/gv/Hv9C//D+Ov6V/fH9i/7g/or/mv8L/3H+Gv7N/fr9cP7j/kb/jf9y/23/h/9t/1r/Wf/H/x8ARQBCAOT/Wf+e/k7+fv6X/u7+T/+a/3j/X/9S/xH/C/+D/3UAQwG6AdEBdAGzAAwA3/95ACYBaQGbAa4BlQH3AF8Ax/9d/1n/xv8AACoA5v8r/yT+Uv5r/n7+qf60/j//1P94/+r+Xf5d/ov+1/4s/1//M//f/nj+J/4E/vT9IP5a/sL+G/8+/+L+fv5S/tL+YP+x/3L/Nv82/z//Of8x/xT/rP5e/lv+k/6H/v/9R/3l/Pr8Df0Z/Tv9Rv0b/RD9T/2+/fn9yP3L/S/+cf5I/jX+OP4n/vf9Av5x/sL+N/6P/WT9q/3Y/QT+Zv6c/on+YP5h/qn+yv6y/lr+Ov43/kr+N/7x/Wr9Z/2f/R/+wv7u/sD+dP5D/ir+F/78/db96/30/Rz+UP5F/uv9u/3h/Xn+J/80/zr/5/4B/23/sP+z/2r/E/8A/zn/Vf8c/4f+Rv61/gn/T/+H/5P/V/80/w==" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 540-543

.. code-block:: default


    display_segment(3)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    CURIOSITY (0.89): 1.127 - 1.851 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 545-548

.. code-block:: default


    display_segment(4)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    BESIDE (0.94): 1.911 - 2.334 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 550-553

.. code-block:: default


    display_segment(5)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    ME (0.67): 2.374 - 2.495 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 555-558

.. code-block:: default


    display_segment(6)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    AT (0.66): 2.535 - 2.595 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 560-563

.. code-block:: default


    display_segment(7)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    THIS (0.70): 2.635 - 2.796 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 565-568

.. code-block:: default


    display_segment(8)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    MOMENT (0.88): 2.877 - 3.159 sec


.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

                    <audio  controls="controls" >
                        <source src="data:audio/wav;base64,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" type="audio/wav" />
                        Your browser does not support the audio element.
                    </audio>
              
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 569-575

Conclusion
----------

In this tutorial, we looked how to use torchaudio’s Wav2Vec2 model to
perform CTC segmentation for forced alignment.



.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  1.665 seconds)


.. _sphx_glr_download_tutorials_forced_alignment_tutorial.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: forced_alignment_tutorial.py <forced_alignment_tutorial.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: forced_alignment_tutorial.ipynb <forced_alignment_tutorial.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_