Subjective Quality Labelled Time-Scale Modification of Audio Dataset

Subjective Quality Labelled Time-Scale Modification of Audio Dataset

This dataset contains source and processed audio files designed primarily for use with Time-Scale Modification (TSM) research.  88 source files were processed at 10 different time-scale ratios by 6 different TSM algorithms resulting in training set of 5280 files.  Each file was then subjectively evaluated by a minimum of 7 participants providing opinion scores.  Mean Opinion Scores (MeanOS) and Median Opinion Scores (MedianOS) are provided for each file.  An additional 20 files were processed at 4 time-scale ratios by an additional 3 methods were also subjectively evaluated resulting in a test set of 240 files.

Instructions: 

Audio files are named using the following structure: SourceName_TSMmethod_TSMratio_per.wav and split into multiple zip files.For TSMmethod, PV is the Phase Vocoder algorithm, PV_IPL is the Identity Phase Locking Phase Vocoder algorithm, WSOLA is the Waveform Similarity Overlap-Add algorithm, FESOLA is the Fuzzy Epoch Synchronous Overlap-Add algorithm, HPTSM is the Harmonic-Percussive Separation Time-Scale Modification algorithm and uTVS is the Mel-Scale Sub-Band Modelling Filterbank algorithm. Elastique is the z-Plane Elastique algorithm, NMF is the Non-Negative Matrix Factorization algorithm and FuzzyPV is the Phase Vocoder algorithm using Fuzzy Classification of Spectral Bins.TSM ratios range from 33% to 192% for training files and 20% to 200% for testing files.

  • Train: Contains 5280 processed files for training neural networks

  • Test: Contains 240 processed files for testing neural networks

  • Ref_Train: Contains the 88 reference files for the processed training files

  • Ref_Test: Contains the 20 reference files for the processed testing files

 

SMOQ_MOS.mat is a version 7 MATLAB save file and contains:

  • Name: A vector of Cells containing audio filenames

  • MeanOS: A vector of Mean Opinion Scores

  • MedianOS: A vector of Median Opinion Scores

 

SMOQ_MOS.csv is a csv containing Names, MeanOS and MedianOS values.Please Note: Labels for the files will be uploaded after paper publication.

Dataset Files

You must login with an IEEE Account to access these files. IEEE Accounts are FREE.

Sign Up now or login.

Embed this dataset on another website

Copy and paste the HTML code below to embed your dataset:

Share via email or social media

Click the buttons below:

facebooktwittermailshare
[1] Timothy Roberts, "Subjective Quality Labelled Time-Scale Modification of Audio Dataset", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/ny9p-rv41. Accessed: Jan. 21, 2020.
@data{ny9p-rv41-20,
doi = {10.21227/ny9p-rv41},
url = {http://dx.doi.org/10.21227/ny9p-rv41},
author = {Timothy Roberts },
publisher = {IEEE Dataport},
title = {Subjective Quality Labelled Time-Scale Modification of Audio Dataset},
year = {2020} }
TY - DATA
T1 - Subjective Quality Labelled Time-Scale Modification of Audio Dataset
AU - Timothy Roberts
PY - 2020
PB - IEEE Dataport
UR - 10.21227/ny9p-rv41
ER -
Timothy Roberts. (2020). Subjective Quality Labelled Time-Scale Modification of Audio Dataset. IEEE Dataport. http://dx.doi.org/10.21227/ny9p-rv41
Timothy Roberts, 2020. Subjective Quality Labelled Time-Scale Modification of Audio Dataset. Available at: http://dx.doi.org/10.21227/ny9p-rv41.
Timothy Roberts. (2020). "Subjective Quality Labelled Time-Scale Modification of Audio Dataset." Web.
1. Timothy Roberts. Subjective Quality Labelled Time-Scale Modification of Audio Dataset [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/ny9p-rv41
Timothy Roberts. "Subjective Quality Labelled Time-Scale Modification of Audio Dataset." doi: 10.21227/ny9p-rv41