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audio
audio | speaker_tags
string | labels
int64 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
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NURC_RE_EF_054 | 36 |
Dataset card
This dataset includes ~80k samples of speech audio in Brazilian Portuguese. Samples have variable length ranging from 1 to 4 seconds, with a sampling rate of 16kHz. The metadata file includes speaker tags and corresponding labels for each sample, making it appropriate for speaker identification and speaker verification tasks.
Dataset Description
Audio samples are taken from three bigger corpora: C-ORAL Brasil, NURC Recife and NURC SP. Please take into consideration the licenses details of the original corpora. All the recordings come from monologues, but there are brief moments of interruption by the researchers that conducted the recordings. The recordings comprise accents from three different states of Brazil: Belo Horizonte, São Paulo and Recife. The dataset is structured in a way that makes it possible to load with HF Audiofolder. In my experience, I noticed that it is easier to clone the dataset repo to your machine and then load it specifying the local data_dir than to load it directly from the hub using the dataset tag.
Dataset Sources
- C-ORAL BRASIL: [https://www.c-oral-brasil.org/c-oral-brasil-i.php]
- NURC Recife: [https://fale.ufal.br/projeto/nurcdigital/index.php?action=home]
- NURC SP: [http://tarsila.icmc.usp.br:8080/nurc/home]
Out-of-Scope Use
The models trained with this dataset should not be used to intentionally create hostile or alienating environments for people.
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