Automatic message correction is a ubiquitous feature of modern optical recognition systems, suggesting possible solutions to eliminate noise in a message transmitted by the user. Efficiency is crucial to ensure that the system has a real-time responsiveness when operating with different writing codes such as letters and/or numbers. Previous works were based on the use of a trie data structure for fast prefix-search operations even if this method is not always accurate as only completions that are prefixed by the query are returned. This paper aims to describe a method for correcting a symbolic music text and discuss its efficiency/effectiveness in relation to other possible approaches. The solution is based on the use of Shannon and Weaver information theory to reconstruct the message, a direction not yet explored in the literature. The solution is based on eliminating noise by inserting musical notes into the musical phrase that allow it to have a low entropy value, corresponding to a high information value. The method has been tested on tonal polyphonic compositions and has given encouraging results. Future improvements of the method and possible applications in other practical areas are briefly discussed at the end of the paper.