Advances in computational power have enabled the manipulation of music audio files and the emergence of the Music Information Retrieval field. One of the main research lines in this area is that of Music Transcription, which aims at transforming an audio file into musical notation. So far, most efforts have focused on accurately transcribing the pitch and durations of the notes, and thus neglecting other aspects in the music score. The present work explores a novel line of action in the context of automatic music transcription, focusing on the dynamics, and by means of Linguistic Description. The process described in this paper (called MUDELD: MUsic Dynamics Extraction through Linguistic Description) departs from the data series representing the audio file, and requires the segmentation of the piece in phrases, which is currently done by hand. Initial experiments have been performed on eight recordings of Debussy's Syrinx with promising results.