# Dataset Card for Dhivehi Presidential Speech 1.0


### Dataset Summary

Dhivehi Presidential Speech is a Dhivehi speech dataset created from data extracted and processed by [Sofwath](https://github.com/Sofwath) as part of a collection of Dhivehi datasets found [here](https://github.com/Sofwath/DhivehiDatasets).

The dataset contains around 2.5 hrs (1 GB) of speech collected from Maldives President's Office consisting of 7 speeches given by President Yaameen Abdhul Gayyoom. 

### 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.

```json
{
  'path': 'dv-presidential-speech-train/waves/YAG2_77.wav',  
  'sentence': 'އަދި އަޅުގަނޑުމެންގެ ސަރަޙައްދުގައިވެސް މިކަހަލަ ބޭބޭފުޅުން',
  'audio': {
    'path': 'dv-presidential-speech-train/waves/YAG2_77.wav', 
    'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32), 
    'sampling_rate': 16000
  }, 
}

```

### Data Fields

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

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

- 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. The test clips were generated from a speech not in the train split. For the validation split, there is a slight overlap of 1 speech in the train set.

|                  | Train    | Validation | Test  |
| ---------------- | -------- | ---------- | ----- |
| Speakers         | 1        | 1          | 1     |
| Utterances       | 1612     | 200        | 200   |
| Duration         | 02:14:59 | 17:02      | 13:30 |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

Extracted and processed by [Sofwath](https://github.com/Sofwath) as part of a collection of Dhivehi datasets found [here](https://github.com/Sofwath/DhivehiDatasets).

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[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

[More Information Needed]

### Contributions

[More Information Needed]
task_categories:automatic-speech-recognition task_categories:text-to-speech size_categories:1K<n<10K language:dv license:apache-2.0 audio dhivehi yag speech president political region:us
{"language": ["dv"], "license": "apache-2.0", "size_categories": ["1K<n<10K"], "task_categories": ["automatic-speech-recognition", "text-to-speech"], "tags": ["audio", "dhivehi", "yag", "speech", "president", "political"]}
TAGS
#task_categories-automatic-speech-recognition #task_categories-text-to-speech #size_categories-1K<n<10K #language-Dhivehi #license-apache-2.0 #audio #dhivehi #yag #speech #president #political #region-us 

Dataset Card for Dhivehi Presidential Speech 1.0
================================================


### Dataset Summary


Dhivehi Presidential Speech is a Dhivehi speech dataset created from data extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here.


The dataset contains around 2.5 hrs (1 GB) of speech collected from Maldives President's Office consisting of 7 speeches given by President Yaameen Abdhul Gayyoom.


### 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.


### Data Fields


* path (string): The path to the audio file.
* sentence (string): The transcription for the audio file.
* 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. The test clips were generated from a speech not in the train split. For the validation split, there is a slight overlap of 1 speech in the train set.



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


Extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here.


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions



### Dataset Summary


Dhivehi Presidential Speech is a Dhivehi speech dataset created from data extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here.


The dataset contains around 2.5 hrs (1 GB) of speech collected from Maldives President's Office consisting of 7 speeches given by President Yaameen Abdhul Gayyoom. ### 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. ### Data Fields


* path (string): The path to the audio file.
* sentence (string): The transcription for the audio file.
* 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. The test clips were generated from a speech not in the train split. For the validation split, there is a slight overlap of 1 speech in the train set.



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization


Extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here. #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions
TAGS
#task_categories-automatic-speech-recognition #task_categories-text-to-speech #size_categories-1K<n<10K #language-Dhivehi #license-apache-2.0 #audio #dhivehi #yag #speech #president #political #region-us 
 ### Dataset Summary


Dhivehi Presidential Speech is a Dhivehi speech dataset created from data extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here.


The dataset contains around 2.5 hrs (1 GB) of speech collected from Maldives President's Office consisting of 7 speeches given by President Yaameen Abdhul Gayyoom. ### 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. ### Data Fields


* path (string): The path to the audio file.
* sentence (string): The transcription for the audio file.
* 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. The test clips were generated from a speech not in the train split. For the validation split, there is a slight overlap of 1 speech in the train set.



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization


Extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here. #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions
passage: TAGS
#task_categories-automatic-speech-recognition #task_categories-text-to-speech #size_categories-1K<n<10K #language-Dhivehi #license-apache-2.0 #audio #dhivehi #yag #speech #president #political #region-us 
### Dataset Summary


Dhivehi Presidential Speech is a Dhivehi speech dataset created from data extracted and processed by Sofwath as part of a collection of Dhivehi datasets found here.


The dataset contains around 2.5 hrs (1 GB) of speech collected from Maldives President's Office consisting of 7 speeches given by President Yaameen Abdhul Gayyoom.### 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.### Data Fields


* path (string): The path to the audio file.
* sentence (string): The transcription for the audio file.
* 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. The test clips were generated from a speech not in the train split. For the validation split, there is a slight overlap of 1 speech in the train set.



Dataset Creation
----------------### Curation Rationale### Source Data