diff --git a/examples/tutorials/forced_alignment_tutorial.py b/examples/tutorials/forced_alignment_tutorial.py
index e0c6a769f7..21f2765f6f 100644
--- a/examples/tutorials/forced_alignment_tutorial.py
+++ b/examples/tutorials/forced_alignment_tutorial.py
@@ -78,7 +78,7 @@
 # Generate frame-wise label probability
 # -------------------------------------
 #
-# The first step is to generate the label class porbability of each audio
+# The first step is to generate the label class probability 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`.
 #
@@ -143,7 +143,7 @@ def plot():
 # :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.
+# The following diagram illustrates this transition.
 #
 # .. image:: https://download.pytorch.org/torchaudio/tutorial-assets/ctc-forward.png
 #