The word vectors are generated randomly from a standard normal distribution with d = 10. d-dimensional word embeddings in an N × d matrix, then apply DCT along the rows.
each feature in the vector space is compressed independently, and the resultant DCT embeddings summarize the feature patterns along the word sequence.