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audioduration (s)
2.16
5.24
speaker
stringclasses
98 values
duration_sec
float64
2.16
5.24
p001
4.145
p001
2.853
p001
2.485
p001
2.285
p001
3.635
p001
3.055
p001
2.995
p001
3.185
p001
4.305
p001
2.335
p001
4.685
p001
2.875
p001
3.445
p001
2.785
p001
3.315
p001
3.605
p001
2.574
p001
5.085
p001
2.386
p001
2.625
p001
2.715
p001
4.585
p001
3.295
p001
4.845
p001
3.755
p001
2.755
p001
3.284
p001
4.005
p001
2.425
p001
2.363
p001
4.265
p001
5.165
p001
2.582
p001
2.835
p001
5.155
p001
2.545
p001
3.605
p001
4.755
p001
3.025
p001
2.755
p001
3.385
p001
4.655
p001
2.785
p001
2.615
p001
2.765
p001
2.825
p001
4.925
p001
5.215
p001
3.255
p001
3.835
p001
3.545
p001
2.575
p001
2.655
p001
2.725
p001
4.065
p001
4.125
p001
5.165
p001
3.715
p001
3.625
p001
4.875
p001
5.185
p001
2.495
p001
2.405
p001
3.675
p001
2.805
p001
3.185
p001
3.675
p001
2.975
p001
2.745
p001
4.735
p001
3.035
p001
2.855
p001
3.225
p001
3.215
p001
5.195
p001
4.475
p001
4.965
p001
4.505
p001
2.785
p001
2.995
p001
2.875
p001
5.155
p001
3.925
p001
4.875
p001
3.335
p001
2.395
p002
3.555
p002
2.295
p002
3.013
p002
2.595
p002
5.065
p002
2.745
p002
4.516
p002
3.445
p002
3.105
p002
4.228
p002
2.775
p002
3.525
p002
5.105
p002
5.115
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EARS naturalistic phrases (2-5 s)

6,153 short naturalistic English phrases (2-5 seconds, median 3.5 s) cut at pause boundaries from the freeform (unscripted) portions of the EARS dataset (Richter et al., Interspeech 2024): the emotional freeform monologues and the unconstrained freeform monologues. Reading tasks, interjections, and non-verbal recordings were excluded.

  • Audio: 48 kHz, mono, 16-bit FLAC (lossless from the source WAV)
  • Speakers: 98 (EARS train speakers p001-p099)
  • Recording: anechoic chamber, studio-grade full-band speech
  • Segmentation: energy-based phrase detection (25 ms frames, 250 ms pause threshold), 120 ms context padding, 10 ms edge fades; segments were QA filtered for level (RMS >= -38 dBFS), clipping (< 0.1% samples), and speech density (>= 55% voiced frames)

License: CC BY-NC 4.0, same as the source dataset. If you use this data, cite the EARS paper:

@inproceedings{richter2024ears,
  title={{EARS}: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation},
  author={Richter, Julius and Wu, Yi-Chiao and Krenn, Steven and Welker, Simon and Lay, Bunlong and Watanabe, Shinjii and Richard, Alexander and Gerkmann, Timo},
  booktitle={ISCA Interspeech},
  year={2024}
}
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