Dataset Viewer
Auto-converted to Parquet Duplicate
text
stringlengths
1
349
subset
stringclasses
2 values
audio
audioduration (s)
1
28.3
duration
float64
1
28.3
ⴷⴰⵔⵉ ⵢⴰⵏ ⵓⵎⵓⴽⵔⵉⵙ
subset_1
1.386667
ⵎⴰⴷ ⴰⴽ ⵉⵙⵎ ?
subset_1
1.450667
ⵉⵙ ⴰⵔ ⴽⴰ ⵙⵎⵓⵇⵇⵓⵍⵖ.
subset_1
1.664
ⵙⵔⵙ ⵉⴼⴰⵙⵙⵏ ⵏⵏⵎ ⴼ ⵓⵖⵔⴰⴱ.
subset_1
1.621333
ⵉⵄⵇⴱ ⴷ ⵙⴰⵎⵉ ⵖⵔ ⵓⵅⵅⴰⵎ.
subset_1
1.984
ⴰⴷ ⵏⵏ ⵓⵔ ⵜⵎⴰⵟⵍⵎ ⴼ ⵜⵉⵏⵎⵍ.
subset_1
2.069333
ⵀⴰ ⵏⵏ ⴽⵢⵢ ⴽⴰ ⵙ ⵏⵙⵙⵓⵎⴷ, ⴷ ⴽⵢⵢ ⴽⴰ ⴰⴷ ⵏⵎⵎⵜⵔ
subset_1
3.328
ⵎⴰⵏ ⵜⵉⵎⵖⵔⵉⵜ ⵖ ⵜⵍⵍⵉⵜ?
subset_1
1.92
ⵉⵙ ⴰⵔ ⵀⵍⵍⵉ ⵜⵜⴼⵉⵔⵔⵉⵢⵏ ⵡⵓⵙⵙⴰⵏ.
subset_1
2.197333
ⵎⴰⵢⵎⵎⵉ ⵜⴹⵚⵚⴰⴷ?
subset_1
1.28
ⴰⵔⴰ ⵙ ⵜⵎⴰⵣⵉⵖⵜ
subset_1
1.322667
ⵓ, ⴱⵓ, ⴳⵓ , ⴷⵓ, ⴹⵓ.
subset_1
5.290667
ⵢⴰⵏ
subset_1
1.536
ⴰⵙⵙ ⵏ ⵜⵍⴰⵍⵉⵜ ⵉⵖⵓⴷⴰⵏ!
subset_1
1.536
ⵎⴰⵎⵛ ⵖⴰ ⴰⵔⵉⵖ ⵜⴰⵙⴽⵍⴰ ⴰ ⵜⵉⵍⵉ ⵙ ⵜⴱⵓⵍⴳⴰⵔⵉⵜ?
subset_1
2.56
ⴽⵔⴰⵢⴳⴰⵜ ⴰⵙⵙ ⴰⵔ ⵉⵜⵜⵛⵓⵛⵓⴼ.
subset_1
1.557333
ⵜⵎⵍⴰ ⵍⴰⵢⵍⴰ ⵉⵜⵍⵉ ⵉ ⵙⴰⵎⵉ.
subset_1
2.090667
ⴷⵉⵏⵏⴰ ⴳ ⵏⵏ ⵜⵍⵍⴰⵎⵜ ⴰⴷ ⴷ ⵜⴰⵙⵎⵜ ⵖⵔ ⴷⴰ.
subset_1
2.069333
ⵛⵛⵉⵖ ⵢⴰⵏ ⵓⴱⴰⵡ ⵉⴹⵏⵏⴰⵟ ⴰⴽⴰⴷ ⵉⵎⵎⵉⵎ.
subset_1
2.432
ⴱⴱ
subset_1
1.301333
ⵉⵔⵡⴰⵙ ⵉⵙ ⴷ ⵏⴽⴽ ⴰⴷ ⵜ ⵉⴳⴰⵏ.
subset_1
1.941333
ⴱⴱⴻ
subset_1
1.066667
ⵙⵔⵙⵏ ⴰⴽⴽⵯ ⵉⵎⴰⴽⵔⵏ ⴰⵢⵍⵍⵉ ⴷⴰⵔⵙⵏ ⵉⵍⵍⴰⵏ ⵔⵡⵍⵏ ⵙ ⴽⵔⴰⵢⴳⴰⵜ ⵜⴰⵙⴳⴰ.
subset_1
3.328
ⵎⴰⵢⵎⵎⵉ ⵓⵔ ⴰⵙ ⵜⵏⵏⵉⵜ ⵖⵉⴽ ⴰⵏⵏ?
subset_1
2.389333
ⴰⵎⵛⵛⵉⵡⵕ.
subset_1
1.152
ⴼⴻ, ⴽⴻ, ⵀⴻ, ⵃⴻ
subset_1
3.648
ⵉⴼⵖⴰⴽⴰⵍⵏ, ⵉⵎⵙⴰⵢⵔⴰⵔⵏ, ⴰⴼⵖⴰⴽⴰⵍ, ⵉⴼⵖⴰⴽⴰⵍⵏ, ⴰⵎⵙⴰⵢⵔⴰⵔ, ⴰⵙⴰⵢⵔⴰⵔ, ⴰⵙⴰⵢⵔⵓⵔ
subset_1
6.912
ⵓⵔ ⵙⵙⵉⵏⵖ ⵎⴰ ⵉⴳⴰ ⴰⵙⴰⴳⵎ ⵏⵏⵙ.
subset_1
2.154667
ⴰⴷ ⴰⴽⴽⵯ ⵓⵔ ⵜⵣⵔⵉⴱⵎⵜ ⵙ ⵜⴽⵏⴰⵔⵉⵜ.
subset_1
2.218667
ⵜⴰⵄⵕⴰⴱⵜ ⴷ ⵜⴼⵕⴰⵏⵙⵉⵙⵜ
subset_1
1.92
ⵢⴰⵖⵖ
subset_1
1.045333
ⵉⵎⴰⵍⵍⴰⵢⵏ ⴰⴷ ⴰⴽⴽⵯ ⴳⴰⵏ.
subset_1
1.664
ⵙⵍⵍⴰⵖ ⵛⴰ ⵉⵜⵜⵓⵙⵓ.
subset_1
1.386667
ⵎⴰⵢⵎⵎⵉ ⵓⵔ ⴰⵙ ⵜⵏⵏⵉⴷ ⵖⵉⴽⴰⵏⵏ?
subset_1
2.432
ⵜⵓⴳⵜ ⴰⴷ ⴷ ⴼⵍⵍⴰⵖ ⵉⵙⵇⵙⴰⵏ.
subset_1
1.770667
ⵜⴹⵕ ⴷ ⵜⴳⵎⵎⵉ.
subset_1
1.578667
ⴰⵙⵉⵏⴰⴳ ⴰⵏⴰⴼⵍⵍⴰ ⵏ ⵜⵏⴱⴹⴰⵢⵜ.
subset_1
2.474667
ⵎⴰⴼ ⴱⴰⵀⵔⴰ ⵜⵇⵇⵉⵎⵎ ⴷⴳ ⴱⵓⵚⵟⵏ?
subset_1
2.261333
ⴰⵔ ⴼⵜⵜⵓⵏ ⵡⵓⵙⵙⴰⵏ ⵙ ⵜⴰⵣⵣⵍⴰ.
subset_1
2.261333
ⴹⵓ
subset_1
1.194667
ⵉⵥⵥⴰ ⵙⴰⵎⵉ ⵍⴰⵢⵍⴰ ⵖ ⵜⴳⵎⵎⵉ.
subset_1
1.92
ⴼⴽⴰⵜ ⵉⵢⵉ ⴰⵎⵓⵔ ⵉⵏⵓ.
subset_1
1.493333
ⴽⴽⵉⵖ ⵜⵜ ⵉⵏⵏ ⵓⵔ ⵙⵙⵉⵏⵖ ⵎⴰ ⵉⴳⴰⵏ ⵜⵉⵣⵉ ⵏ ⵓⵙⵓⵏⴼⵓ
subset_1
2.837333
ⵡⴰⴷ ⴷ ⴰⵎⴷⴷⴰⴽⵯⵍ ⵉⵏⵓ
subset_1
1.514667
ⴳⴳⴰⵡⵔⵖ ⴳ ⵜⴳⵎⵎⵉ ⴰⵛⴽⵓ ⵢⵓⵜ ⵉⵢⵉ ⵡⴰⴹⵓ.
subset_1
2.432
ⵜⵡⵜⵎⵜ ⵜ?
subset_1
1.130667
ⵎⴰⴷ ⴰⵖ ⵢⴰⵖⵏ
subset_1
1.152
ⵇⵇⴰⴷ ⵉⵜⵜⵡⴰⵣⵎⵎⴰⵎ ⴳ ⵢⴰⵜ ⵜⵙⴰⵡⵔⵜ ⵏ ⵜⵥⵓⵕⵉ.
subset_1
2.581333
ⵢⴰⵡⵡ
subset_1
1.493333
ⵛⴽⴽ ⴷ ⴰⵏⴱⵔⴰⵣ ⵏⵏⵖ.
subset_1
1.429333
ⵉⵙⵙⵏ ⴰⴷ ⵉⵙⴰⵡⴰⵍ.
subset_1
1.493333
ⵎⴰⵅⵅ ⵍⵍⵉⵖ ⴱⴰⵀⵔⴰ ⵜⵖⴰⵎⴰⵎ ⴳ ⴱⵓⵚⵟⵏ?
subset_1
2.432
ⵜⴽⴽⴰ ⵜⵜ ⵉⵏⵏ ⵍⴰⵢⵍⴰ ⴰⵔ ⵜⵍⵙⵙⴰ ⵢⴰⵜ ⵜⴽⵔⴱⵜ ⵉⵙⴳⴳⴰⵏⵏ.
subset_1
2.773333
ⵏⴽⴽ ⴳⵉⵖ ⵉⵎⵉⵖⵉⵙ ⴳ ⵜⵎⴰⵙⵙⴰⵏⵉⵏ.
subset_1
2.304
ⵓⵔ ⴷⴰⵔⵉ ⵉⴽⵔⵉⵙⵏ ⴷ ⵜⴰⴷ.
subset_1
2.112
ⴰⵔ ⴱⴷⴷⴰ ⴷⵉⴷⵏⵖ ⵜⵜⵉⵍⵉⵏ.
subset_1
1.557333
ⵉⵔⴳⴳⵉⴳ ⵙⵓⵍ ⵓⵏⵣⵡⵉ ⴳ ⵍⵉⵏⴳⵍⵉⵣ ⴼ ⵙⴽⵓⵜⵍⴰⵏⴷⴰ.
subset_1
2.730667
ⵢⴰⵠ
subset_1
1.109333
ⵢⴰⴹⴹ
subset_1
1.344
ⵀⴰ ⵜ ⵓⵔ ⵖⵉⴷ ⵜⵔⵖⵉ ⵎⴽⵍⵍⵉ ⵢⴰⴷ ⵍⵍⵉ ⵜⴰⵎⵖ.
subset_1
2.325333
ⵎⵎⵓⵜⵏ ⵢⴰⵏ ⵙ ⵢⴰⵏ.
subset_1
1.472
ⴰⵡⴷ ⵢⴰⵏ ⵓⵔ ⴰⵔ ⵉⴹⵚⵚⴰ.
subset_1
1.749333
ⵏⴽⴽⵏⵉ ⵓⵔ ⵜ ⵏⵙⵙⵉⵏ.
subset_1
1.749333
ⵜⴰⵎⴰⵣⵉⵖⵜ ⵜⵍⵍⴰ ⴳ ⵎⵓⵔⴰⴽⵓⵛ, ⴷⵣⴰⵢⵔ, ⵍⵉⴱⵢⴰ ⴷ ⵙⵉⵡⴰ.
subset_1
3.818667
ⵎⴰⵏⵉⴽ ⴰ ⵙ ⵜⵙⵙⵏⴷ?
subset_1
1.408
ⴰⴽⴰⵍ ⴷ ⵉⵥⵕⴰⵏ ⴰⴷ ⴷ ⵙⵓⵍ ⵢⴰⴳⵓⵔⵏ ⴳ ⵜⴰⴷⴷⴰⵔⵜ ⵏⵏⵖ ⵍⵍⵉⵖ ⵜⵜ ⵊⴷⵔⵏ ⴰⵢⵜ ⵓⵙⵓⵏ.
subset_1
4.352
ⴰⵔⴳⴰⵣ ⵏⵏⵙ ⴷ ⴰⵣⵡⴰⵡⵉ.
subset_1
1.664
ⴰⵊⵊⴰⵎⵜ ⵉⵢⵉ ⴰⴷ ⴼⴼⵖⵖ!
subset_1
2.005333
ⵉⵙⵍⵍⴰ ⵙⴰⵎⵉ ⵉ ⵓⵙⵓⵙⵔ ⵉⵙⵍⵍ ⵉ ⵓⵎⵙⵍⵉ ⵏ ⵢⴰⵏ ⵓⵔⴳⴰⵣ ⴳ ⴹⴰⵕⴰⵜ.
subset_1
3.413333
ⵎⴰⴷ ⵉⴳⴰ ⵜⴰⵖⴰⵡⵙⴰ ⵍⵍⵉ ⴰⴽⴽⵯ ⵉⴼⵓⵍⴽⵉⵏ ⵜⵙⴽⵔⴷ ⵜⵜ ⴳ ⵜⵓⴷⵔⵜ ⵏⵏⴽ?
subset_1
3.797333
ⵢⴰⵇ
subset_1
1.493333
ⵎⵓⵏⵖ ⴷ ⵉⵙⵜⵎⴰ ⵙ ⴷⴰⵔ ⵢⴰⵜ ⵜⵏⴰⵔⴰⴳⵜ ⵏⵏⵖ.
subset_1
2.474667
ⴰⴷ ⵏ ⵓⵔ ⵜⵎⴰⵟⵍⵎ ⴼ ⵜⵉⵏⵎⵍ.
subset_1
1.642667
ⵖⵔⵏⵖ ⴰⵟⵟⴰⵚ ⵏ ⵉⵏⴷⵓⴷⵉⵢⵏ ⴳ ⵊⵊⴰⴱⴱⵓⵏ.
subset_1
2.432
ⵎⵏⵛⴽ ⴰⴷ ⵉⴳⴰ ⵡⴰⵜⵉⴳ ⵏ ⵜⵀⵉⵔⵉⵜ ⴰⴽⴽⵯ ⵉⵖⵯⵍⴰⵏ.
subset_1
2.645333
ⵎⴰⵏⵉ ⵣⴰ ⵙⵓⵍ ⵏⵔⴰ.
subset_1
1.301333
ⵀⴰⵜ ⵏⵏⵉⵖ ⵙ ⵓⵖⵉⵍⵓⴼ.
subset_1
1.621333
ⵜⴰⵎⴰⵡⴰⵙⵜ ⵏ ⵜⵣⵔⴼⵜ.
subset_1
1.642667
ⵔⵉⵖ ⵓⴽⴰⵏ ⴰⴷ ⴰⵎ ⵄⴰⵕⴷⵖ ⵙ ⵢⵉⵡⵉⵣ.
subset_1
2.496
ⴰⵏⵙⵙⵉⵅⴼ ⵏ ⵜⵏⴱⴰⴹⵜ.
subset_1
1.301333
ⴰⵔ ⵜⵜ ⵜⴻⵜⵜⵉⵏⵉⴷ ⴽⵔⴰⵢⴳⴰⵜ ⴰⵙⵙ
subset_1
2.069333
ⵃⴰⵇⵇⴰⵏ ⵉⵙ ⴷ ⴷⵉⴽ ⵎⵙⴰⵛⴽⴰⵏ ⴽⵔⴰ ⵏ ⵉⵡⴷⴰⵏ.
subset_1
2.624
ⵏⴽⴽ ⴰⵔ ⵙⴰⵡⴰⵍⵖ ⵙ ⵜⵎⴰⵣⵉⵖⵜ
subset_1
2.043356
ⵙⵓⵍ ⵓⴽⴰⵏ ⵏⴷⴷⵔ.
subset_1
1.664
ⴰⵔ ⵉⵊⴷⴷⵔ ⵓⴽⵛⵛⵓⴹ.
subset_1
1.706667
ⴷ ⴰⵙⵍⵎⴰⴷ ⵏ ⵜⵓⴱⵉⵔⵜ.
subset_1
1.92
ⵎⴰⴷ ⴰⵡⴰ ⴳⵉⵙ ⵜⵔⵉⴷ?
subset_1
1.408
ⵓⵍⵉ ⴰⵙ ⵉⴷⴰⵎⵎⵏ ⵉ ⵄⵣⵣⵉ.
subset_1
2.026667
ⵉⴹⴳⴰⵎ ⴰⴷ ⵏⵖⵉⵖ ⵢⴰⵜ ⵜⴰⴽⴽⴰⵍⵜ ⴳ ⵜⴳⵎⵎⵉ ⵏⵏⵖ.
subset_1
2.901333
ⵍⴱⴷⴰ ⵜⵜⵉⵍⵉⵏ ⴰⴽⵉⴷⵏⵖ.
subset_1
1.621333
ⵀⴰⵜⵉ ⴰⵔ ⵜⵜⵡⴰⵔⴳⴰⴷ?
subset_1
1.642667
ⴼⴼⴰ
subset_1
1.194667
ⵎⵍ ⵉⵢⵉ ⵎⴰⴷ ⴷ ⵜⴻⵜⵜⵎⵓⵏⴷ ⴰⴷ ⴰⴽ ⵎⵍⵖ ⵎⴰⴷ ⵜⴳⵉⴷ.
subset_1
2.176
ⴳⴳⴻ
subset_1
1.152
ⵓⵔ ⵉⴳⵉ ⵖⴰⵙ ⴽⵢⵢ ⵡⴰⵢⵏⵏⵉ ⵀⴰⵜ ⴰⵡⴷ ⵏⴽⴽ ⵉⵔⴰ ⵉⵢⵉ ⵏⵏ ⵡⴰⴷⴷⴰⴷ.
subset_1
2.901333
ⵉⵙ ⵉⵍⵍⴰ ⵓⴱⵓⴱⴱⴰⵥ ⴳ ⵜⵉⵥⴳⵉ ⴰ?
subset_1
2.304
ⵢⵓⵖⴰⵍ ⴷ ⵙⴰⵎⵉ ⵙ ⵜⴰⴷⴷⴰⵔⵜ.
subset_1
2.176
ⵖⴰⵢⵏ ⴰ ⴼ ⴷ ⵜⵓⵛⴽⵉⴷ ⵙ ⵖⵉⵏ?
subset_1
1.749333
ⵓⵙⵔⵖ ⴽⵔⴰ ⵏ ⵓⵖⴰⵏⵉⴱ.
subset_1
1.429333
ⵜ, ⵜⴰ, ⵜⵓ, ⵜⵉ, ⵜⴻ
subset_1
4.053333
End of preview. Expand in Data Studio

Dataset Card for Tamazight Open Speech Dataset

This dataset provides a parsed, formatted, and ready-to-use Amazigh Voice Dataset. It contains voice recordings and corresponding text transcripts in Standard Moroccan Amazigh (ⵜⴰⵎⴰⵣⵉⵖⵜ ⵜⴰⵏⴰⵡⴰⵢⵜ ⵜⴰⵎⵓⵔⴰⴽⵓⵛⵜ) intended for training Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models.

This specific repository is published by a collaborator. You may visit the raw dataset repository which has additional dataset that hasn't been uploaded here yet: Amazigh-Speech-Dataset.

Dataset Details

Dataset Sources

Uses

Direct Use

  • Training or fine-tuning Speech-to-Text (STT / ASR) models.
  • Training or fine-tuning Text-to-Speech (TTS) models.
  • Linguistic research regarding Amazigh phonetics and speech.

Out-of-Scope Use

This data should not be used to generate malicious voice clones or deepfakes intended for impersonation, fraud, or harassment.

Dataset Structure

Unlike the raw dataset which uses separate .wav and .txt files in .zip archives, this dataset has been parsed into a structured format for immediate use with the Hugging Face datasets library.

It contains 1,801 examples with the following fields:

  • audio: The audio data feature, containing the decoded audio array and sampling rate.
  • text: The string transcript of the audio in the Tifinagh script.
  • duration: The length of the audio clip in seconds (float64).
  • subset: The dataset has two different subsets recorded using different microphones. While subset_1 has mono audio, subset_2 is stereo.

Dataset Creation

Curation Rationale

Amazigh is a low-resource language in AI. This dataset was created to contribute high-quality, openly licensed voice data to help the open-source community build better voice technologies for the Amazigh-speaking community.

Source Data

Data Collection and Processing

The audio was recorded by a fluent speaker reading from pre-selected Standard Moroccan Amazigh texts. This specific repository hosts the processed and structured version of those original recordings.

Who are the source data producers?

The audio was originally recorded by Abdelhaque Id Ali, a speaker of Southern Moroccan Amazigh.

Personal and Sensitive Information

The dataset contains the voice recordings of the creator. No other personally identifiable information (PII) is included in the audio or text.

Bias, Risks, and Limitations

This dataset represents the voice, accent, and pronunciation of a single speaker using Standard Moroccan Amazigh. It may not fully capture the phonetic diversity of other regional Amazigh varieties. Models trained solely on this data may struggle with accents or dialects not represented here.

Dataset Card Authors

Dataset Card Contact

Downloads last month
101

Collection including Tamazight-NLP/TOSD