diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/arm/pass/convert_group_conv1d.hpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/arm/pass/convert_group_conv1d.hpp
index 7790f68df6b819..37905dc63f5b1c 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/arm/pass/convert_group_conv1d.hpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/arm/pass/convert_group_conv1d.hpp
@@ -10,7 +10,7 @@
  *     ConvertConv1DBase detects 1D Convolution / GroupConvolution and replaces
  *     it with the sequence Unsqueeze - 2D Convolution / GroupConvolution - Squeeze.
  *     Unsqueeze adds the additional dimension to Convolution inputs and Squeeze 
- *     removes the additional dimention from the Convolution output.
+ *     removes the additional dimension from the Convolution output.
  *
  * Before:
  * 
diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/convert_fq_rnn_to_quantized_rnn.cpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/convert_fq_rnn_to_quantized_rnn.cpp
index 9bb4367f6f2d01..c943adfd39ac4f 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/convert_fq_rnn_to_quantized_rnn.cpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/convert_fq_rnn_to_quantized_rnn.cpp
@@ -104,7 +104,7 @@ ov::intel_cpu::ConvertFqRnnToQuantizedRnn::ConvertFqRnnToQuantizedRnn() {
             const auto& cell_state = pattern_map.at(cell_state_m);
             const auto& sequence_length = pattern_map.at(sequence_length_m);
 
-            // @todo prototype removal of unnecessary fq between two consequtive rnn nodes
+            // @todo prototype removal of unnecessary fq between two consecutive rnn nodes
             auto rnn_quantized_tr = std::make_shared<op::TypeRelaxed<ngraph::opset9::LSTMSequence>>(
                 element::TypeVector{ element::f32, element::f32, element::f32, element::f32, element::f32, element::f32, element::f32 },
                 element::TypeVector{ element::f32, element::f32, element::f32 },
diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/fc_bias_fusion.cpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/fc_bias_fusion.cpp
index b257c127590b7c..03fe3e76f486a5 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/fc_bias_fusion.cpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/fc_bias_fusion.cpp
@@ -76,9 +76,9 @@ ov::intel_cpu::NonQuantizedFullyConnectedBiasFusion::NonQuantizedFullyConnectedB
     this->register_matcher(m, callback);
 }
 
-//CPU plugin would config LPT  not to propogate dequantization scale over bias to follow ONEDNN 3.x scheme.
+//CPU plugin would config LPT  not to propagate dequantization scale over bias to follow ONEDNN 3.x scheme.
 //It is a little tricky now to first fuse bias not DQ for pattern "FC + DQ + BIAS".
-//todo: Will move the FullyConnnect fusing into CPU and fuse the DQ and BIAS in topology order.
+//todo: Will move the FullyConnect fusing into CPU and fuse the DQ and BIAS in topology order.
 ov::intel_cpu::QuantizedFullyConnectedBiasFusion::QuantizedFullyConnectedBiasFusion() {
     MATCHER_SCOPE(FullyConnectedBiasFusion);
     auto input = ngraph::pattern::any_input();
diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
index f883f382696f56..3ec6980f420758 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
@@ -43,7 +43,7 @@ inline void ConvertToCPUSpecificOpset(std::shared_ptr<ngraph::Function> &nGraphF
     if (!ov::op::util::has_op_with_type<ngraph::op::FakeQuantize>(nGraphFunc)) {
         CPU_REGISTER_PASS_COMMON(manager, ReshapeFullyConnectedFusion);
     }
-    // after transformation "MoveEltwiseUpThroughDataMov" there can be Reshape sequences that should be eliminated or fused
+    // after transformation "MoveEltwiseUpThroughDataMov" there can be reshaped sequences that should be eliminated or fused
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ReshapeSequenceFusion);
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ConstantFolding);
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ConvertPrecision, precisions_map {{ ngraph::element::i64, ngraph::element::i32 }});