Sentence examples for onset detection from inspiring English sources

Fig. 1 Block diagram commonly used for onset detection.

For all approaches, the relevant parameters are separately optimized for three tasks: monophonic onset detection (songs without accompaniment), predominant onset detection where we are just interested in the melody onsets, and onset detection where we are interested in all onsets.

Sequential model-based optimization (MBO) is applied to find optimal parameter settings for three considered variants of onset detection: (1) monophonic, (2) polyphonic, and (3) predominant onset detection.

In particular, onset detection is still rather error-prone for polyphonic music [20].

Furthermore, we propose parameter optimization to adapt the method to predominant onset detection.

The results for onset detection are disappointing, but this is also true for the reference approach.

Table 6 shows the results of onset detection for the three considered approaches: (1) common onset detection on the original signal (without any auditory model), (2) onset detection using the auditory model output by choosing the output of the best single channel, and (3) onset detection where the estimated onset time points of several channels are combined.

A more advanced discussion of onset detection in multiple frequency bands is presented in [24].

It is within this context that onset detection will be studied in this article.

A comprehensive list of onset detection and selection algorithms has also been considered.

In [17], note onset detection instead of beat tracking is used for music segmentation.