DescriptionWith its substantial improvement in storage and processing power over traditional audio media,
the MP3 player has quickly become the standard for portable audio devices. These improvements
have allowed for enhanced services such as album artwork display and video playback. Anothersuch service that could be offered on today's MP3 players is the synchronized display of song lyrics.
The goal of this thesis is to show that this can be implemented efficiently using the techniques of HMM based speech recognition. Two assumptions are made that simplify this process. First, we assume that the lyrics to any song can be obtained and stored on the device along with the audio file. Second, the processing can be done just once when the song is initially loaded, and the time indices indicating word start times can also be stored and used to guide the synchronized lyrical display. Several simplified cases of the lyrical alignment problem are implemented and tested here.
Two separate models are trained, one containing a single male vocalist with no accompaniment, and another containing the same vocalist with simple guitar accompaniment. Model parameters are varied to examine their effect on alignment performance, and the models are tested using independent audio files containing the same vocalist and additional vocal and guitar accompaniment. The test configurations are evaluated for objective accuracy, by comparison to manually determined word start times, and subjective accuracy, by carrying out a perceptual test in which users rate the perceived quality of alignment. In all but one of the test configurations evaluated here, a high level of objective and subjective accuracy is achieved. While well short of a commercially viable lyrical
alignment system, these results suggest that with further investigation the approach outlined here can in fact produce such a system to effectively align an entire music library.