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+ =====================================================================================================
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+
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+ ASVspoof5 Database
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+
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+ Copyright (c) 2024
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+
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+ ASVspoof5 organizing committee
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+ https://www.asvspoof.org/
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+
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+ =====================================================================================================
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+
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+ 1. Directory Structure
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+ _______________________
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+
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+ This package includes
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+ |- flac_T_aa.tar ASVspoof 5 training set data
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+ |...
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+ |- flac_T_ae.tar
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+ |
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+ |- flac_D_aa.tar ASVspoof 5 development set data
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+ |...
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+ |- flac_D_ac.tar
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+ |
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+ |- flac_E_aa.tar ASVspoof 5 evaluation set sdata
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+ |...
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+ |- flac_E_aj.tar
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+ |
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+ |- ASVspoof5_protocols.tar.gz ASVspoof 5 protocol and file lists
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+ |
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+ |- LICENSE.txt
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+ |- README.txt
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+
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+
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+ By unpacking flac_T_**.tar, a new directory flac_T will be created, and the training set speech data will be saved in ./flac_T
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+
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+ By unpacking flac_D_**.tar, a new directory flac_D will be created, the development set speech data will be saved in ./flac_D
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+
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+ By unpacking flac_E_**.tar, a new directory flac_E_eval will be created, the evaluation set speech data will be saved in ./flac_E_eval
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+
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+ By unpacking ASVspoof5_protocols.tar.gz, the following files will be extracted
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+ |
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+ |- ASVspoof5.train.tsv list of training set utterances, keys, and other information
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+ |
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+ |- ASVspoof5.dev.track_1.tsv list of development set utterances, keys, and other information.
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+ | It can be used for model validation in track 1 (detection model without ASV)
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+ |
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+ |- ASVspoof5.dev.trial.txt list of ASV trials created from development set data.
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+ | It can be used for model validation in track 2 (Spoofing robust ASV)
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+ |
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+ |- ASVspoof5.dev.enroll.txt list of enrollment utterances of targets speaker
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+ | in the development set
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+ |
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+ |- ASVspoof5.eval.track_1.tsv list of evaluation set utterances, keys, and other information.
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+ | It is used for track 1 evaluation
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+ |
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+ |- ASVspoof5.eval.trial.tsv list of ASV trials created from evaluation set data.
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+ | It is used for track 2 evaluation
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+ |
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+ |- ASVspoof5.eval.enroll.tsv list of enrollment utterances of targets speaker
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+ | in the evaluation set
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+ |
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+ |- ASVspoof5.codec.config.csv configurations of codec
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+
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+
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+
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+ 2. Statistics and md5sum
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+ _______________________
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+
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+ md5sum filename number_of_lines
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+ b0cc86b14826a7701b52aad4f53daf9c ASVspoof5_train/flac_T_aa.tar 36500
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+ d05be3f4be7a343fdbdd0ed29fdff2e1 ASVspoof5_train/flac_T_ab.tar 36500
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+ 70d1ba4ad75a20aef3dae541fbd321e3 ASVspoof5_train/flac_T_ac.tar 36500
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+ c9bb56af2cc410d98338d74babcb95c9 ASVspoof5_train/flac_T_ad.tar 36500
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+ a3969816982f3e52300d6147ad796df7 ASVspoof5_train/flac_T_ae.tar 36357
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+ df0be44957623991028cce59792beb17 ASVspoof5_dev/flac_D_aa.tar 47400
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+ 1e8cd685d89b64502692f1bcf1a13db3 ASVspoof5_dev/flac_D_ab.tar 47400
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+ 5e0031f08c30e4bdbf0c59f91b2d662b ASVspoof5_dev/flac_D_ac.tar 47334
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+ a8c800766f3d4ef87971e2b4f29663e2 ASVspoof5_eval/flac_E_aa.tar 68188
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+ c35064188f54f07c87aba58de22534a0 ASVspoof5_eval/flac_E_ab.tar 68188
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+ ed7cbcd1b2847998b72472ddf6b445e3 ASVspoof5_eval/flac_E_ac.tar 68188
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+ 626a080e994b05df49c577d7b3dede8d ASVspoof5_eval/flac_E_ad.tar 68188
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+ 05f19a5e64fa556714ae1b38eb2ea70b ASVspoof5_eval/flac_E_ae.tar 68188
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+ 2ca2f52a3bbf827f7ec155ecb47e85d6 ASVspoof5_eval/flac_E_af.tar 68188
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+ 671200b5de2fc1e74a563b07b057af8f ASVspoof5_eval/flac_E_ag.tar 68188
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+ eaf885b1299a61eb07f71e82e96dba37 ASVspoof5_eval/flac_E_ah.tar 68188
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+ b2625683bf440abae2af901a45542ad9 ASVspoof5_eval/flac_E_ai.tar 68188
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+ c50281c8233af6f3b0899604d21ade44 ASVspoof5_eval/flac_E_aj.tar 68180
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+
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+ 865d0e894ea9f686f0f37e5ae3ae3616 ASVspoof5_protocols.tar.gz
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+ cbfa08e2fab1423e828f102bc97a22f0 ASVspoof5.train.tsv 182357
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+ e949dee1091a49b04943c548b5cf9860 ASVspoof5.dev.track_1.tsv 140950
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+ 11d144e71599f455265bfaa229a3168f ASVspoof5.dev.track_2.enroll.tsv 398 (1184 utt.)
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+ 86b20750e7df2c5607401a98225b8606 ASVspoof5.dev.track_2.trial.tsv 282456
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+ 50c0591d45a282cb787a5a4614394f67 ASVspoof5.eval.track_1.tsv 680774
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+ fb754cb8905e7d0816cccaca2d8ffd5f ASVspoof5.eval.track_2.enroll.tsv 367 (1098 utt.)
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+ de83d6de35d80b58e932fe4ecfccc6e4 ASVspoof5.eval.track_2.trial.tsv 834536
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+
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+
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+ Note
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+ a. Speech waveform data are in FLAC format (https://en.wikipedia.org/wiki/FLAC).
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+ The sampling rate is 16 kHz.
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+
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+ b. In total,
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+ flac_T_*.tar: 182357 utterances
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+ flac_D_*.tar: 142134 utterances
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+ = 140950 in ASVspoof5.dev.track_1.tsv + 1184 in ASVspoof5.dev.track_2.enroll.tsv
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+ flac_E_*.tar: 681872 utterances
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+ = 680774 in ASVspoof5.eval.track_1.tsv + 1098 in ASVspoof5.eval.track_2.trial.tsv
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+
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+
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+
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+ 3. Meta data in txt file
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+ _______________________
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+
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+ ASVspoof5.*.tsv are space-separated
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+
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+ ASVspoof5.train.tsv, ASVspoof5.dev.track_1.tsv and ASVspoof5.eval.track_1.tsv have FIVE columns:
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+
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+ SPEAKER_ID FLAC_FILE_NAME SPEAKER_GENDER CODEC CODEC_Q CODEC_SEED ATTACK_TAG ATTACK_LABEL KEY TMP
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+
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+ SPEAKER_ID: T_****, D_****, or E_**** ID of the speaker in the FLAC file
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+ FLAC_FILE_NAME: T/D/E_********** name of the FLAC file
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+ SPEAKER_GENDER: F or M gender of the speaker
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+ CODEC: C** or - name of the codec or compressor condition
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+ CODEC_Q: N or - codec quality factor configuration number
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+ CODEC_SEED: T/D/E_********** or - if this utterance is coded, name of the original utterance
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+ ATTACK_TAG: AC* or - tag of the attacker adaptation condition
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+ ATTACK_LABEL: A** or bonafide name of the attack
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+ KEY: spoof or bonafide CM key
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+ TMP: - reserved column
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+
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+
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+ ASVspoof5.dev.track_2.trial.tsv and ASVspoof5.eval.track_2.trial.tsv have FIVE columns:
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+
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+ TARGET_SPEAKER_ID FLAC_FILE_NAME TARGET_GENDER ATTACK_LABEL ASV_KEY
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+
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+ TARGET_SPEAKER_ID: D_**** or E_**** ID of the ASV target speaker
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+ FLAC_FILE_NAME: D_********** or E_*********** name of the FLAC file
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+ TARGET_GENDER: F or M gender of the target speaker
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+ ATTACK_LABEL A** or bonafide Label of the attack or bonafide
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+ ASV_KEY: target, nontarget, or spoof ASV label
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+
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+
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+
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+ ASVspoof5.dev.enroll.tsv and ASVspoof5.eval.enroll.tsv have TWO columns:
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+
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+ TARGET_SPEAKER_ID FLAC_FILE_NAMES
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+
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+ TARGET_SPEAKER_ID: D/E_**** ID of the ASV target speaker
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+ FLAC_FILE_NAMES: D/E_******,D/E_*****,D/E_***** name of the FLAC files for enrollment
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+
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+ Note
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+ a. FLAC_FILE_NAMES in ASVspoof5.*.enroll.tsv is list of file names separated by ','.
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+ Some target speakers may have less than 3 enrollment utterances
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+
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+ b. The first column in ASVspoof5.*.track_2.trial.tsv is the ID of the target speaker.
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+ The first column in ASVspoof5.*.track_1.tsv and ASVspoof5.train.tsv is the actual speaker ID in the utterance.
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+ The actual speaker may not be equal to the target speaker when the utterance is used in a
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+ non-target AsV trial
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+
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+ c. ASVspoof5.*.track_2.trial.tsv contains limited information on each probe utterance.
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+ You may retrieve information (e.g., CODEC) from the corresponding ASVspoof5.*.track_1.tsv
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+
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+ d. for codec quality and the corresponding bit rates, please check ASVspoof5.codec.config.csv
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+
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+
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+ 4. Copyright and License
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+ ________________________
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+
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+ You are free to use this database under Open Data Commons Attribution License (ODC-By).
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+
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+ Regarding Open Data Commons Attribution License (ODC-By), please see
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+ https://opendatacommons.org/licenses/by/1.0/index.html
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+
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+ THIS DATABASE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS DATABASE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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+
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+ The bona fide data is distributed under CC BY 4.0 Deed | Attribution 4.0 International.
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+ Please see https://creativecommons.org/licenses/by/4.0/
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+
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+
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+ 5.Ethics
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+ ______________________
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+
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+ ASVspoof 5 is committed to upholding ethical standards and to responsible research practices. Our objective is to enhance the security and reliability of automatic speaker verification (ASV) technology by promoting collaboration and progress in the development of robust spoofing/deepfake detection solutions, to promote participation and to protect the interests of stakeholders.
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+
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+ Data contributors and challenge participants are requested to adhere to local data protection regulations when processing speech data. We ask that you conduct your research and development activities in a responsible manner and be mindful of the potential for the misuse of software solutions and results. You are expected to disclose identified vulnerabilities or weaknesses in ASV technology in a responsible manner. The prompt and appropriate reporting of such findings is the shared responsibility of all in our community, contributes to the improvement of security systems and protects against potential misuse.
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+
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+ The ASVspoof organisers explicitly disassociate themselves from any association with or endorsement of hacking activities, unauthorized access attempts, or the creation of spoofs/deepfakes for malicious purposes or personal gain. We strictly condemn any misuse of the knowledge and tools developed through ASVspoof. Any malicious use of challenge outcomes, results or findings is strictly prohibited.
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+
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+ Please note that the ISCA Code of Ethics, available at https://www.isca-speech.org/iscaweb/index.php/about-isca?id=279, applies to all research publications and reports originating from
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+ the ASVspoof initiative and challenge series.
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+
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+
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+ 6. Citation
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+ ______________________
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+
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+ Please cite the following papers if you use ASVspoof5 database
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+
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+ PLACEHOLDER_FOR_DATABASE_PAPER
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+
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+
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+
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+ Wang, X., Delgado, H., Tak, H., Jung, J.-w., Shim, H.-j., Todisco, M., Kukanov, I., Liu, X., Sahidullah, M., Kinnunen, T.H., Evans, N., Lee, K.A., Yamagishi, J. (2024) ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale. Proc. The Automatic Speaker Verification Spoofing Countermeasures Workshop (ASVspoof 2024), 1-8, doi: 10.21437/ASVspoof.2024-1
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+
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+ @inproceedings{wang24_asvspoof,
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+ title = {ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale},
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+ author = {Xin Wang and Héctor Delgado and Hemlata Tak and Jee-weon Jung and Hye-jin Shim and Massimiliano Todisco and Ivan Kukanov and Xuechen Liu and Md Sahidullah and Tomi H. Kinnunen and Nicholas Evans and Kong Aik Lee and Junichi Yamagishi},
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+ year = {2024},
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+ booktitle = {The Automatic Speaker Verification Spoofing Countermeasures Workshop (ASVspoof 2024)},
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+ pages = {1--8},
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+ doi = {10.21437/ASVspoof.2024-1},
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+ }
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+
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+
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+
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+ 7. Acknowledgements
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+ ______________________
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+
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+ This database is based on Multilingual LibriSpeech (MLS) [1].
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+
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+ The spoofed data are created by many contributors, and they will be co-authors of a database-description paper.
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+
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+ [1] V. Pratap, Q. Xu, A. Sriram, G. Synnaeve, and R. Collobert, “MLS: A large-scale multilingual dataset for speech research,” in Proc. Interspeech, 2020. doi: 10.21437/Interspeech.2020-2826.
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+