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audio/T001_A08_03103_0.ogg
audio/T001_A0F_02513_0.ogg
audio/T001_A0X_00483_0.ogg
audio/T001_A5U_00553_0.ogg
audio/T001_A68_01734_0.ogg
audio/T001_A73_01400_0.ogg
audio/T001_A73_02165_0.ogg
audio/T001_A74_02567_0.ogg
audio/T001_A7A_02061_0.ogg
audio/T001_A7F_00783_0.ogg
audio/T001_A7K_01102_0.ogg
audio/T001_AAW_00088_0.ogg
audio/T001_AB9_00458_0.ogg
audio/T001_ABH_00432_0.ogg
audio/T001_ABX_01966_0.ogg
audio/T001_AC6_01870_0.ogg
audio/T001_ACG_00457_0.ogg
audio/T001_ACH_01120_0.ogg
audio/T001_ACV_02484_0.ogg
audio/T001_ACV_02484x2_0.ogg
audio/T001_ACV_02665_0.ogg
audio/T001_ADD_00716_0.ogg
audio/T001_AE7_00632_0.ogg
audio/T001_AK2_00963_0.ogg
audio/T001_ALJ_00893_0.ogg
audio/T001_AMS_00099_0.ogg
audio/T001_AN7_00604_0.ogg
audio/T001_ANK_01389_0.ogg
audio/T001_ANU_00921_0.ogg
audio/T001_AP5_00768_0.ogg
audio/T001_APE_01385_0.ogg
audio/T001_APL_00456_0.ogg
audio/T001_ARJ_03119_0.ogg
audio/T001_ARR_00101_0.ogg
audio/T001_ASB_01241_0.ogg
audio/T001_ASD_02649_0.ogg
audio/T001_AYK_01153_0.ogg
audio/T001_AYK_01153x2_0.ogg
audio/T001_AYP_01479_0.ogg
audio/T001_B04_01339_0.ogg
audio/T001_B1X_02209_0.ogg
audio/T001_B20_01599_0.ogg
audio/T001_B20_02074_0.ogg
audio/T001_B23_01979_0.ogg
audio/T001_B2E_01217_0.ogg
audio/T001_B2F_00351_0.ogg
audio/T001_B32_02020_0.ogg
audio/T001_B78_01683_0.ogg
audio/T001_BMR_01945_0.ogg
audio/T001_BP0_01208_0.ogg
audio/T001_BP0_01208x2_0.ogg
audio/T001_BP0_01499_0.ogg
audio/T001_BP0_02529_0.ogg
audio/T001_BPB_01272_0.ogg
audio/T001_C85_01685_0.ogg
audio/T001_C8D_02493_0.ogg
audio/T001_C8E_01884_0.ogg
audio/T001_C9J_01990_0.ogg
audio/T001_C9R_01388_0.ogg
audio/T001_CA0_01102_0.ogg
audio/T001_CA0_01848_0.ogg
audio/T001_CA3_02157_0.ogg
audio/T001_CA8_00146_0.ogg
audio/T001_CAM_00642_0.ogg
audio/T001_CAM_01699_0.ogg
audio/T001_CAT_00130_0.ogg
audio/T001_CB6_00219_0.ogg
audio/T001_CBC_12380_0.ogg
audio/T001_CBF_01724_0.ogg
audio/T001_CBG_10917_0.ogg
audio/T001_CBN_00489_0.ogg
audio/T001_CBN_02385_0.ogg
audio/T001_CBX_03010_0.ogg
audio/T001_CBY_00369_0.ogg
audio/T001_CCC_00488_0.ogg
audio/T001_CCM_02637_0.ogg
audio/T001_CDA_02564_0.ogg
audio/T001_CDA_03134_0.ogg
audio/T001_CDA_03211_0.ogg
audio/T001_CDB_01483_0.ogg
audio/T001_CDE_00762_0.ogg
audio/T001_CDN_01242_0.ogg
audio/T001_CEM_01571_0.ogg
audio/T001_CEY_00137_0.ogg
audio/T001_CEY_01811_0.ogg
audio/T001_CF4_01200_0.ogg
audio/T001_CF4_01200x2_0.ogg
audio/T001_CF9_01290_0.ogg
audio/T001_CFS_00017_0.ogg
audio/T001_CFY_00364_0.ogg
audio/T001_CFY_00364x2_0.ogg
audio/T001_CGC_00641_0.ogg
audio/T001_CH2_09201_0.ogg
audio/T001_CH4_00948_0.ogg
audio/T001_CH6_05198_0.ogg
audio/T001_CHA_03031_0.ogg
audio/T001_CHR_00062_0.ogg
audio/T001_CJA_02001_0.ogg
audio/T001_CJF_01368_0.ogg
audio/T001_CJF_02523_0.ogg
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Clarity Speech Corpus

This is a mirror of the Clarity Speech Corpus. The original files were converted from WAV to Opus to reduce the size and accelerate streaming.

Usage

import io

import soundfile as sf
from datasets import Features, Value, load_dataset

for item in load_dataset(
    "philgzl/clarity",
    streaming=True,
    features=Features({"audio": Value("binary"), "name": Value("string")}),
):
    print(item["name"])
    buffer = io.BytesIO(item["audio"])
    x, fs = sf.read(buffer)
    # do stuff...

Citation

@article{cox2022clarity,
  title = {Dataset of {British} {English} speech recordings for psychoacoustics and speech processing research: {The} {Clarity} {Speech} {Corpus}},
  author = {Simone Graetzer and Michael A. Akeroyd and Jon Barker and Trevor J. Cox and John F. Culling and Graham Naylor and Eszter Porter and Rhoddy Viveros-Mu{\~{n}}oz},
  journal = {Data Br.},
  volume = {41},
  pages = {107951},
  year = {2022},
}
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