OMRAS2 Music Analysis and Feature Extraction Service

This simple service permits analysis and feature extraction of uploaded audio files using Vamp plugins available on the system.
You might be interested in using SAWA-recommender, a music similarity search engine built on this system.

Overview

You can upload one or more audio files and select one or more of the available Vamp plugin transforms. (At least one file and one selected transform is required.)
The service accepts a number of file formats including .wav and .mp3. The results are returned for each file in RDF or some human readable rendering.
Please follow the processing steps outlined below. Note that some steps are optional.

	Processing steps: 

	1. Upload one or more audio files	
	2. Identify the audio file using MusicIP (optional)
	3. Choose analysis (a Vamp plugin transform)
	4. Configure analysis (optional)
	5. Run Feature extractor (submit query)
	6. Wait for the computation to complete
	7. View Results using one of the output modules (RDF, CSV, Annotated waveform, Score, etc..)

File upload

Please upload an audio file:

filename:

Identify the file and cache resulting features (default).
This is just a test. Please do not identify the file or cache any features.

According to our copyright policy, uploaded files will be deleted as the session expires.

Available plugins

Please select at least one VAMP plugin transform.
You can switch between compact or detailed view of plugin outputs using: toggle outputs.

Vamp Example Plugins

Spectral Centroid   Calculate the centroid frequency of the spectrum of the input signal  Select Output Description Configuration Log Frequency Centroid Centroid of the log weighted frequency spectrum configure this transform Linear Frequency Centroid Centroid of the linear frequency spectrum configure this transform Simple Percussion Onset Detector   Detect percussive note onsets by identifying broadband energy rises  Select Output Description Configuration Detection Function Broadband energy rise detection function configure this transform Onsets Percussive note onset locations configure this transform Simple Fixed Tempo Estimator   Study a short section of audio and estimate its tempo, assuming the tempo is constant  Select Output Description Configuration Detection Function Onset detection function configure this transform Tempo candidates Possible tempo estimates, one per bin with the most likely in the first bin configure this transform Tempo Estimated tempo configure this transform Autocorrelation Function Autocorrelation of onset detection function configure this transform Filtered Autocorrelation Filtered autocorrelation of onset detection function configure this transform Zero Crossings   Detect and count zero crossing points  Select Output Description Configuration Zero Crossings The locations of zero crossing points configure this transform Zero Crossing Counts The number of zero crossing points per processing block configure this transform Simple Power Spectrum   Return the power spectrum of a signal  Select Output Description Configuration Power Spectrum Power values of the frequency spectrum bins calculated from the input signal configure this transform Amplitude Follower   Track the amplitude of the audio signal  Select Output Description Configuration Amplitude configure this transform

qm-vamp-plugins

Tempo and Beat Tracker   Estimate beat locations and tempo  Select Output Description Configuration Tempo Locked tempo estimates configure this transform Beats Estimated metrical beat locations configure this transform Onset Detection Function Probability function of note onset likelihood configure this transform Polyphonic Transcription   Transcribe the input audio to estimated notes  Select Output Description Configuration Transcription Estimated note pitch (MIDI note number from 0 to 127) configure this transform Constant-Q Spectrogram   Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio  Select Output Description Configuration Constant-Q Spectrogram Output of constant-Q transform, as a single vector per process block configure this transform Chromagram   Extract a series of tonal chroma vectors from the audio  Select Output Description Configuration Chromagram Output of chromagram, as a single vector per process block configure this transform Chroma Means Mean values of chromagram bins across the duration of the input audio configure this transform Discrete Wavelet Transform   Visualisation by scalogram  Select Output Description Configuration Wavelet Coefficients Wavelet coefficients configure this transform Mel-Frequency Cepstral Coefficients   Calculate a series of MFCC vectors from the audio  Select Output Description Configuration Coefficients MFCC values configure this transform Means of Coefficients Mean values of MFCCs across duration of audio input configure this transform Key Detector   Estimate the key of the music  Select Output Description Configuration Tonic Pitch Tonic of the estimated key (from C = 1 to B = 12) configure this transform Key Mode Major or minor mode of the estimated key (major = 0, minor = 1) configure this transform Key Estimated key (from C major = 1 to B major = 12 and C minor = 13 to B minor = 24) configure this transform Key Strength Plot Correlation of the chroma vector with stored key profile for each major and minor key configure this transform Note Onset Detector   Estimate individual note onset positions  Select Output Description Configuration Smoothed Detection Function Smoothed probability function used for peak-picking configure this transform Note Onsets Perceived note onset positions configure this transform Onset Detection Function Probability function of note onset likelihood configure this transform Tonal Change   Detect and return the positions of harmonic changes such as chord boundaries  Select Output Description Configuration Tonal Change Detection Function configure this transform Transform to 6D Tonal Content Space configure this transform Tonal Change Positions configure this transform Segmenter   Divide the track into a sequence of consistent segments  Select Output Description Configuration Segmentation Segmentation configure this transform Adaptive Spectrogram   Produce an adaptive spectrogram by adaptive selection from spectrograms at multiple resolutions  Select Output Description Configuration Output The output of the plugin configure this transform Similarity   Return a distance matrix for similarity between the input audio channels  Select Output Description Configuration Distance Matrix Distance matrix for similarity metric. Smaller = more similar. Should be symmetrical. configure this transform Distance from First Channel Distance vector for similarity of each channel to the first channel. Smaller = more similar. configure this transform Feature Means Means of the feature bins. Feature time (sec) corresponds to input channel. Number of bins depends on selected feature type. configure this transform Feature Variances Variances of the feature bins. Feature time (sec) corresponds to input channel. Number of bins depends on selected feature type. configure this transform Beat Spectra Rhythmic self-similarity vectors (beat spectra) for the input channels. Feature time (sec) corresponds to input channel. Not returned if rhythm weighting is zero. configure this transform Ordered Distances from First Channel Vector of the order of other channels in similarity to the first, followed by distance vector for similarity of each to the first. Smaller = more similar. configure this transform Bar and Beat Tracker   Estimate bar and beat locations  Select Output Description Configuration Bars Bar locations configure this transform Beat Count Beat counter function configure this transform Beats Beat locations labelled with metrical position configure this transform Beat Spectral Difference Beat spectral difference function used for bar-line detection configure this transform

SessionID = a970c54dfd375d3d07e8189fbef1c369f05af813