Transcribing audio recordings into written scores is a method musicians and musicologists use to comprehend better music that is notated, such as traditional folk music and improvised jazz solos. Using signal-processing techniques to extract pitch and rhythm information from recordings, automatic music transcription greatly accelerates and automates the transcription process. Even for professionals, this process has historically required extensive musical skills and takes time. Therefore, this study tackles the unresolved issue of automated music transcription by offering a comprehensive approach to tackle its most intricate subtask—multiple-pitch estimation. Given the difficulty of recognizing and transcribing simultaneous notes in polyphonic music, multiple-pitch estimation is essential. An extensive analysis of a standard multiple-pitch estimates algorithm and a discussion of its shortcomings round out the study. Even with these developments, there are still many challenges facing automatic music transcription, especially when effectively transcribing polyphonic music. The study highlights the intricacy and continuing nature of research in this subject by emphasizing that despite advancements, considerable work needs to be done to get accurate and reliable machine transcribing.