In an attempt to understand what acoustic/auditory feature sets motivated transcribers towards certain labeling decisions, I built machine learning models that were capable of discriminating between canonical and non-canonical vowels excised from the Buckeye Corpus. Specifically, I wanted to model when the dictionary form and the transcribed-form…

Systematic differences among regional U.S. English speech are recognizable to native speakers to varying degrees. This has been demonstrated by researchers in perceptual dialectology who ask listeners to match a speaker to his or her dialect region. Machines have also been able to identify the regional origin of a speaker to some degree, although…

Recognition and separation of sounds played by various instruments is very useful in labeling audio files with semantic information. This is a non-trivial task requiring sound analysis, but the results can aid automatic indexing and browsing music data when searching for melodies played by user specified instruments. Melody match based on pitch…