Datasets:
audio
audioduration (s) 0
2.4
| speaker
stringclasses 21
values | duration
float64 0.28
2.4
| gender
stringclasses 2
values | text
stringclasses 758
values |
---|---|---|---|---|
COE_13 | 0.416 | M | o*a |
|
COE_13 | 0.356 | M | oʔa |
|
COE_13 | 0.337 | M | oʔa |
|
COE_13 | 0.924 | M | pinimɨ̃ |
|
COE_13 | 0.675 | M | pinimõ |
|
COE_13 | 0.94 | M | pinimɨ̃ |
|
COE_13 | 0.646 | M | kʰo*ɨme |
|
COE_13 | 1.15 | M | kʰoɨme |
|
COE_13 | 0.835 | M | kʰoɨme |
|
COE_13 | 0.542 | M | wese |
|
COE_13 | 0.573 | M | wese |
|
COE_13 | 0.432 | M | ɲjaˀseˀ |
|
COE_13 | 0.547 | M | ɲjaˀse |
|
COE_13 | 0.562 | M | ɲjaˀseˀ |
|
COE_13 | 0.736 | M | cimo |
|
COE_13 | 1.066 | M | cimo |
|
COE_13 | 1.348 | M | cimo |
|
COE_13 | 0.643 | M | makaɾɨ |
|
COE_13 | 0.696 | M | makaɾɨ |
|
COE_13 | 0.626 | M | makaɾɨ |
|
COE_13 | 0.816 | M | siuɲjɨ |
|
COE_13 | 0.772 | M | siuɲjɨ |
|
COE_13 | 0.821 | M | siuɲjɨ |
|
COE_13 | 0.865 | M | coˀcomɨ̃ |
|
COE_13 | 0.663 | M | coˀcomẽ |
|
COE_13 | 0.778 | M | coˀcomɨ̃ |
|
COE_13 | 0.652 | M | ɨ*ɨmɨ̃ |
|
COE_13 | 0.607 | M | ɨ*ɨmɨ̃ |
|
COE_13 | 0.547 | M | ɨ*ɨmɨ̃ |
|
COE_13 | 0.75 | M | iɦace |
|
COE_13 | 0.663 | M | iɦace |
|
COE_13 | 0.622 | M | iɦace |
|
COE_13 | 0.903 | M | ca*o |
|
COE_13 | 1.154 | M | ca*o |
|
COE_13 | 0.652 | M | ca*o |
|
COE_13 | 1.029 | M | kaimɨ̃ |
|
COE_13 | 0.895 | M | kaimɨ̃ |
|
COE_13 | 0.854 | M | kaimɨ̃ |
|
COE_13 | 0.645 | M | maɲa |
|
COE_13 | 0.587 | M | maɲa |
|
COE_13 | 0.625 | M | maɲa |
|
COE_13 | 0.975 | M | casamɨ̃ |
|
COE_13 | 1.124 | M | cɨcɨ |
|
COE_13 | 0.685 | M | cɨˀcɨ |
|
COE_13 | 0.715 | M | cɨˀcɨ |
|
COE_13 | 0.938 | M | ka |
|
COE_13 | 0.413 | M | ka |
|
COE_13 | 0.649 | M | ka |
|
COE_13 | 0.884 | M | tʰeˀteɨ |
|
COE_13 | 1.12 | M | teteɨ |
|
COE_13 | 0.703 | M | tʰeteɾɨ |
|
COE_13 | 0.578 | M | βito |
|
COE_13 | 0.529 | M | βito |
|
COE_13 | 0.512 | M | βito |
|
COE_13 | 0.533 | M | cio |
|
COE_13 | 0.623 | M | cio |
|
COE_13 | 0.616 | M | cio |
|
COE_13 | 0.724 | M | koɨo |
|
COE_13 | 0.59 | M | koɨo |
|
COE_13 | 0.534 | M | koɨo |
|
COE_13 | 0.684 | M | ca*i |
|
COE_13 | 0.896 | M | ca*i |
|
COE_13 | 0.615 | M | sɨ̃sɨ |
|
COE_13 | 0.577 | M | sɨ̃sɨ |
|
COE_13 | 0.512 | M | sɨ̃sɨ |
|
COE_13 | 0.639 | M | ca*i |
|
COE_13 | 1.549 | M | poɦace |
|
COE_13 | 0.886 | M | poɦace |
|
COE_13 | 1.234 | M | poɦace |
|
COE_13 | 0.968 | M | casamɨ̃ |
|
COE_13 | 0.877 | M | peumɨ̃ |
|
COE_13 | 0.629 | M | peˀumɨ̃ |
|
COE_13 | 0.597 | M | peumɨ̃ |
|
COE_13 | 0.815 | M | casamɨ̃ |
|
COE_13 | 0.561 | M | βeβɨ |
|
COE_13 | 0.636 | M | βeβɨ |
|
COE_13 | 0.551 | M | βeβɨ |
|
COE_13 | 0.727 | M | siˀswemɨ̃ |
|
COE_13 | 0.674 | M | siˀswemɨ̃ |
|
COE_13 | 0.681 | M | siˀswemɨ̃ |
|
COE_13 | 0.554 | M | hena |
|
COE_13 | 0.566 | M | hena |
|
COE_13 | 0.581 | M | hena |
|
COE_13 | 0.884 | M | ukupiamɨ̃ |
|
COE_13 | 0.979 | M | ceˀcome |
|
COE_13 | 1.131 | M | ceˀcome |
|
COE_13 | 0.735 | M | caˀcomẽ |
|
COE_13 | 0.89 | M | kʰweˀkomɨ̃ |
|
COE_13 | 0.679 | M | kweˀkomɨ̃ |
|
COE_13 | 0.84 | M | kweˀkomɨ̃ |
|
COE_13 | 0.828 | M | ukupia*mɨ̃ |
|
COE_13 | 0.537 | M | ha*a |
|
COE_13 | 0.55 | M | h*a |
|
COE_13 | 0.55 | M | ha*a |
|
COE_13 | 0.687 | M | βeβeɲɨ̃ |
|
COE_13 | 0.705 | M | βeβeɲɨ̃ |
|
COE_13 | 0.664 | M | βeβeɲɨ̃ |
|
COE_13 | 0.821 | M | ukupiamɨ̃ |
|
COE_13 | 0.727 | M | onona |
|
COE_13 | 0.624 | M | onona |
End of preview. Expand
in Dataset Viewer.
This is a Korebaju language dataset under construction.
check https://github.com/YuDZEN/korebaju-ASR for the Kaldi and MFA project for the same project
Audio Data
Audio data is in the audio
folder. The audio data is in the wav
format.
Transcription Data
Transcription data is test.jsonl
and train.jsonl
in the racine folder. The transcription data is in the jsonl
format.
Data Split
The data is split into train
and test
sets.
The train
set contains 90% of the data and the test
set contains 10% of the data.
data augmentation
We used data augmentation in order to increase the diversity of our training data without actually collecting new data (we have a very small dataset). By applying noise and volume, we can generate some training samples, which are named by "_NOISE" or "_VOLUME" after speakers' names.
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