dash8x's picture
- Updated audio files to 48KHz
e6bc8f0
metadata
license: apache-2.0
task_categories:
  - automatic-speech-recognition
  - text-to-speech
language:
  - dv
tags:
  - audio
  - dhivehi
  - speech
  - khadheeja
  - narrated
size_categories:
  - 1K<n<10K

Dataset Card for Dhivehi Khadheeja Speech 1.0

Dataset Summary

Dhivehi Khadheeja Speech is a single speaker Dhivehi speech dataset created by Javaabu Pvt. Ltd..

The dataset contains around 20 hrs of text read by professional Maldivian narrator Khadheeja Faaz. The text used for the recordings were text scrapped from various Maldivian news websites.

Supported Tasks and Leaderboards

  • Automatic Speech Recognition
  • Text-to-Speech

Languages

Dhivehi

Dataset Structure

Data Instances

A typical data point comprises the path to the audio file and its sentence.

{
  'path': 'dhivehi-khadheeja-speech-train/waves/khadeejafaaz_6_1498pmzd.wav',  
  'sentence': 'އެއްވެސް ފިޔަވަޅެއް އެޅި ކަން އެނގިވަޑައިގެންފައި ނުވާ ކަމަށާއި އެފަދަ ފިޔަވަޅެއް އަޅާފައިވާ ނަމަ އެކަން',
  'sentence_normalized': 'އެއްވެސް ފިޔަވަޅެއް އެޅި ކަން އެނގިވަޑައިގެންފައި ނުވާ ކަމަށާއި އެފަދަ ފިޔަވަޅެއް އަޅާފައިވާ ނަމަ އެކަން',
  'audio': {
    'path': 'dhivehi-khadheeja-speech-train/waves/khadeejafaaz_6_1498pmzd.wav', 
    'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32), 
    'sampling_rate': 48000
  }, 
}

Data Fields

  • path (string): The path to the audio file.

  • sentence (string): The transcription for the audio file.

  • sentence_normalized (string): The normalized transcription for the audio file with digits normalized to text.

  • audio (dict): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0].

Data Splits

The speech material has been subdivided into portions for train, test and validation.

Train Validation Test Total
Utterances 9307 1164 1164 11635
Duration 15:49:13 01:59:46 02:11:28 20:00:27

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

Data was collected through the AduEhy TTS Management System developed Javaabu. The narrator was shown text snippets one at a time, which were then read and recorded through the browser. Text normalization has been performed, which involved replacing multiple whitespaces and new lines with single spaces and converting digits to spoken form.

Who are the source language producers?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@misc{Javaabu_2023, 
    title = "Dhivehi Khadheeja Speech Dataset", 
    url = "https://huggingface.co/datasets/javaabu/dhivehi-khadheeja-speech", 
    journal = "Hugging Face",
    author = {{Javaabu Pvt. Ltd.}}, 
    year = "2023", 
    month = jul
} 

Contributions