Update README.md

README.md

@@ -59,7 +59,7 @@ This syntactic complexity measure focuses on measuring the number of words per s
 
 
 * **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).
 
 
@@ -67,7 +67,7 @@ This syntactic complexity measure focuses on measuring the number of words per s
 
 
 * **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.