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* **Automated Readability Index (ARI)**: Senter and Smith, in 1967, proposed one of the most used indexes due to its ease of calculation, the *Automated Readability Index*, better known as ARI. This index measures the difficulty of a text from the average number of characters (letters and numbers) per word and the average number of words per sentence. * **Automated Readability Index (ARI)**: Senter and Smith, in 1967, proposed one of the most used indexes due to its ease of calculation, the *Automated Readability Index*, better known as ARI. This index measures the difficulty of a text from the average number of characters (letters and numbers) per word and the average number of words per sentence.
* **Dependency tree depth*: This measure was proposed by Saggion et al. in 2015. It is a very useful metric to capture syntactic complexity: long sentences can be syntactically complex or contain a large number of modifiers (adjectives, adverbs or adverbial phrases). It complements the ASL measure, as it captures syntactic complexity in terms of recursive or nested structures. * **Dependency tree depth**: This measure was proposed by Saggion et al. in 2015. It is a very useful metric to capture syntactic complexity: long sentences can be syntactically complex or contain a large number of modifiers (adjectives, adverbs or adverbial phrases). It complements the ASL measure, as it captures syntactic complexity in terms of recursive or nested structures.
* **Punctuation Marks*: This measure was also proposed by Saggion et al. In the complexity of a text, the average number of punctuation marks is used as one of the indicators of the simplicity of the text. * **Punctuation Marks*: This measure was also proposed by Saggion et al. In the complexity of a text, the average number of punctuation marks is used as one of the indicators of the simplicity of the text.
* **Readability of Fernández-Huerta*: Blanco (2002) and Ramirez (2013) propose this measure of complexity as an adaptation to Spanish of Flesch's readability test (Flesch, 1948). * **Readability of Fernández-Huerta**: Blanco (2002) and Ramirez (2013) propose this measure of complexity as an adaptation to Spanish of Flesch's readability test (Flesch, 1948).
* **Readability of Flesch-Szigrist (IFSZ)*: The works of Barrio et al. (2008) and Ramírez et al. (2013) propose the Flesch-Szigristzt readability index as a modification of the Flesch formula adapted to Spanish by Szigriszt-Pazos in 1993. This index is currently considered a reference for the Spanish language. It focuses on measuring the number of syllables per word and the number of sentences per word in the text. * **Readability of Flesch-Szigrist (IFSZ)**: The works of Barrio et al. (2008) and Ramírez et al. (2013) propose the Flesch-Szigristzt readability index as a modification of the Flesch formula adapted to Spanish by Szigriszt-Pazos in 1993. This index is currently considered a reference for the Spanish language. It focuses on measuring the number of syllables per word and the number of sentences per word in the text.
* **Comprehensibility of Gutiérrez de Polini*: This metric, originally developed in 1972, is not an adaptation of English, but was created from the beginning for Spanish (Rodriguez, 1980). It focuses on measuring the average number of letters per word and the average number of words per sentence. * **Comprehensibility of Gutiérrez de Polini**: This metric, originally developed in 1972, is not an adaptation of English, but was created from the beginning for Spanish (Rodriguez, 1980). It focuses on measuring the average number of letters per word and the average number of words per sentence.
* **$\mu$ Readability*: It is a formula to calculate the readability of a text. It provides an index between 0 and 100 and was developed by Muñoz in 2006. This measure focuses on measuring the number of words, the average number of letters per word and their variance. * **$\mu$ Readability**: It is a formula to calculate the readability of a text. It provides an index between 0 and 100 and was developed by Muñoz in 2006. This measure focuses on measuring the number of words, the average number of letters per word and their variance.
* **Minimum age to understand*: In work of García (2001) we can find another formula to measure the age needed to understand a text. It is, again, an adaptation into Spanish of Flesch's original formula for English. It measures the average number of syllables per word and the average number of words per sentence to obtain the minimum age needed to understand a text. * **Minimum age to understand**: In work of García (2001) we can find another formula to measure the age needed to understand a text. It is, again, an adaptation into Spanish of Flesch's original formula for English. It measures the average number of syllables per word and the average number of words per sentence to obtain the minimum age needed to understand a text.
* **SOL Readability*: Contreras et al. (1999) proposes the SOL metric as an adaptation to Spanish of the SMOG formula proposed by Mc Laughlin (1969). It measures the readability of a text by means of grade level, which is the number of years of schooling required to understand the text. * **SOL Readability**: Contreras et al. (1999) proposes the SOL metric as an adaptation to Spanish of the SMOG formula proposed by Mc Laughlin (1969). It measures the readability of a text by means of grade level, which is the number of years of schooling required to understand the text.
* **Years Crawford*: This measure was proposed by Alan N. Crawford in 1989. It is used to calculate the years of school required to understand a text. Measures the number of sentences per hundred words and the number of syllables per hundred words. * **Years Crawford**: This measure was proposed by Alan N. Crawford in 1989. It is used to calculate the years of school required to understand a text. Measures the number of sentences per hundred words and the number of syllables per hundred words.
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