Update src/frontends/tensorflow_lite/src/sparsity_info.cpp

Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>

src/frontends/tensorflow_lite/src/sparsity_info.cpp

@@ -13,17 +13,17 @@ bool ov::frontend::tensorflow_lite::SparsityInfo::is_copyable() const {
 // Unpacks sparse data. Supports only case when sparse tensor has only one sparse dimension [DENSE, ..., DENSE, SPARSE]
 // TensorFlow Lite uses a specific format for storing sparse data (TACO):
 // It uses three 1D arrays/1D tensors/vectors:
-// values - stored in a model's buffers
-// segments/postions - list of row's start positions
+// values - stored in model's buffers
+// segments/positions - list of row's start positions
 // indices - list of value indexes in a row (size is equal to values)
-// Algorithm is next, and it should be easily modified later for 2D spare matrices (that's why it uses a 2D approach):
+// Algorithm is next, and it should be easily modified later for 2D sparse matrices (that's why it uses a 2D approach):
 // 1. Get a first segment position, set idx = 0
 // In a cycle
 // 2. Get next segment position
 // 3. Get an element_count by a difference between current segment position and last_segment position.
 //    If diff between last and current segment is 0 it means an empty row (contains only default values).
 //    In cycle for each element in a segment:
-//    4. Caclulate a row_offset using idx-th index by indeces and element_size (fp16/fp32/etc...)
+//    4. Calculate a row_offset using idx-th index by indices and element_size (fp16/fp32/etc...)
 //    5. Put an idx-th value to a found target dest + row_offset
 //    6. Move to a next row
 template <typename T, typename U>