  We propose a dataset, AVASpeech-SMAD, to assist speech and music activity
detection research. With frame-level music labels, the proposed dataset extends
the existing AVASpeech dataset, which originally consists of 45 hours of audio
and speech activity labels. To the best of our knowledge, the proposed
AVASpeech-SMAD is the first open-source dataset that features strong polyphonic
labels for both music and speech. The dataset was manually annotated and
verified via an iterative cross-checking process. A simple automatic
examination was also implemented to further improve the quality of the labels.
Evaluation results from two state-of-the-art SMAD systems are also provided as
a benchmark for future reference.
