Kurt's Works

In large audio collections, it is common to store audio content with perceptual encoding. However, encoding
parameters may vary from collection to collection or even within a collection - using different bit rates,
sample rates, codecs, etc. We evaluate the effect of various audio encodings on the onset detection task.
We show that audio-based onset detection methods are surprisingly robust in the presence of MP3 encoded
audio. Statistically significant changes in onset detection accuracy only occur at bit-rates lower than 32kbps.

In large audio collections, it is common to store audio content using perceptual encoding. However, encoding
parameters may vary from collection to collection or even within a collection - using different bit rates, sample
rates, codecs, etc. We evaluate the effect of various lossy audio encodings on the application of audio spectrum
projection features to the automatic genre classification tasks. We show that decreases in mean classification
accuracy, while small, are statistically significant for bit-rates of 96kbps or lower. Also, a heterogeneous

[10/2007] Paper for the 123rd AES convention in which we match drum loops against a database of unheard music signals to automatically apply a text label describing the rhythmic style of the music signal PDF