ITCLDATA-ANJan 13, 2022

Optimal alphabet for single text compression

arXiv:2201.05234v23 citations
AI Analysis

This work addresses the problem of efficient text compression for data storage and transmission, but it is incremental as it builds on existing Huffman coding methods by comparing different alphabets.

The study investigated which alphabet (letters, n-grams, syllables, words, or phrases) minimizes the full code length for text compression, including the codebook, finding that syllables or words are optimal for most Project Gutenberg texts, with compact codebook representation improving performance for large alphabets.

A text written using symbols from a given alphabet can be compressed using the Huffman code, which minimizes the length of the encoded text. It is necessary, however, to employ a text-specific codebook, i.e. the symbol-codeword dictionary, to decode the original text. Thus, the compression performance should be evaluated by the full code length, i.e. the length of the encoded text plus the length of the codebook. We studied several alphabets for compressing texts -- letters, n-grams of letters, syllables, words, and phrases. If only sufficiently short texts are retained, an alphabet of letters or two-grams of letters is optimal. For the majority of Project Gutenberg texts, the best alphabet (the one that minimizes the full code length) is given by syllables or words, depending on the representation of the codebook. Letter 3 and 4-grams, having on average comparable length to syllables/words, perform noticeably worse than syllables or words. Word 2-grams also are never the best alphabet, on the account of having a very large codebook. We also show that the codebook representation is important -- switching from a naive representation to a compact one significantly improves the matters for alphabets with large number of symbols, most notably the words. Thus, meaning-expressing elements of the language (syllables or words) provide the best compression alphabet.

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