The goal of this research project is two-fold: first, to conduct a statistical analysis of internal landmarks within the LaMIT framework, and second, to develop a system for automatic landmark identification. The project aims to apply the Lexical Access model conceived by Stevens [Stevens, K. N. (2002). “Toward a model for lexical access based on acoustic landmarks and distinctive features,” J. Acoust. Soc. of Am., 111(4):1872–1891] to the Italian language and enhance it with automatic detection capabilities. The project proposes to apply Stevens’ Lexical Access model to the Italian language and statistically analyze the internal landmarks within the LaMIT framework. This analysis aims to provide insights into the universal and language-specific features of acoustic landmarks. Additionally, the project aims to develop a system for the automatic identification of landmarks in the Italian language, designed to imitate the listener’s process of deriving intended words from a speaker, involving creating a speech recognizer based on acoustic landmarks and distinctive features. Modeling this process requires hypothesizing how lexical items are stored in memory. Stevens’ model postulates that lexical items are stored in memory according to distinctive features, hierarchically organized. The model highlights the importance of abrupt acoustic events, named landmarks, in the perception process, with detection of landmarks being primary in human perception, corresponding to the first phase of recognition, followed by further processing of the temporal area around the landmark by the listener. The expected outcomes include understanding the universal and language-specific features by applying the Lexical Access model to Italian, uncovering universal, language-independent aspects and understanding specific features of the Italian language. Additionally, developing an Italian speech recognizer based on landmarks and acoustic features detection will establish a significant reference system for the speech community in Europe and beyond, offering access to data and algorithms to support further research and applications in speech perception. The project ambitiously aims to understand whether language-independent mechanisms exist in the above process and to discriminate them against language-dependent ones, hypothesizing that cues to landmarks may be language-independent. Supported evidence for universal strategies of speech perception would lead to a significant impact. The acoustical analyses will use the xkl software tool developed by Dennis Klatt at MIT. This project holds the potential to significantly impact the field of speech perception by providing evidence for universal strategies and developing valuable resources for the Italian language.