Speech and Noise Corpora for Pitch Estimation of Human Speech
Part of the dissertation Pitch of Voiced Speech in the Short-Time Fourier Transform: Algorithms, Ground Truths, and Evaluation Methods. © 2020, Bastian Bechtold. All rights reserved. This dataset contains common speech and noise corpora for evaluating fundamental frequency estimation algorithms as c...
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| Format: | Dataset |
| Language: | English |
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2020
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| Online Access: | https://zenodo.org/record/3921794 https://doi.org/10.5281/zenodo.3921794 |
| Summary: | Part of the dissertation Pitch of Voiced Speech in the Short-Time Fourier Transform: Algorithms, Ground Truths, and Evaluation Methods. © 2020, Bastian Bechtold. All rights reserved. This dataset contains common speech and noise corpora for evaluating fundamental frequency estimation algorithms as convenient JBOF dataframes. Each corpus is available freely on its own, and allows redistribution: CMU-ARCTIC (BSD license) [1] FDA (free to download) [2] KEELE (free for noncommercial use) [3] MOCHA-TIMIT (free for noncommercial use) [4] PTDB-TUG (ODBL license) [5] NOISEX (free to download) [7] QUT-NOISE (CC-BY-SA license) [8] Additionally, this dataset contains PDAs-0.0.1-py3-none-any.whl, a Python ≥ 3.6 module for Linux, containing several well-known fundamental frequency estimation algorithms: AUTOC [9] AMDF [10] BANA [11] CEP [12] CREPE [13] DIO [14] DNN [15] KALDI [16] MAPS MBSC [17] NLS [18] PEFAC [19] PRAAT [20] RAPT [21] SACC [22] SAFE [23] SHR [24] SIFT [25] SRH [26] STRAIGHT [27] SWIPE [28] YAAPT [29] YIN [30] The algorithms are included in their native programming language (Matlab for BANA, DNN, MBSC, NLS, NLS2, PEFAC, RAPT, RNN, SACC, SHR, SRH, STRAIGHT, SWIPE, YAAPT, and YIN; C for KALDI, PRAAT, and SAFE; Python for AMDF, AUTOC, CEP, CREPE, MAPS, and SIFT), and adapted to a common Python interface. AMDF, AUTOC, CEP, and SIFT are our partial re-implementations as no original source code could be found. All algorithms have been released as open source software, and are covered by their respective licenses. All of these files are published as part of my dissertation, "Pitch of Voiced Speech in the Short-Time Fourier Transform: Algorithms, Ground Truths, and Evaluation Methods", and in support of the Replication Dataset for Fundamental Frequency Estimation. References: John Kominek and Alan W Black. CMU ARCTIC database for speech synthesis, 2003. Paul C Bagshaw, Steven Hiller, and Mervyn A Jack. Enhanced Pitch Tracking and the Processing of F0 Contours for Computer Aided Intonation Teaching. In EUROSPEECH, ... |
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