dataset_info:
features:
- name: audio
dtype: audio
- name: sentence
dtype: string
- name: phonemes
dtype: string
splits:
- name: train
num_bytes: 754910024.376
num_examples: 3336
- name: test
num_bytes: 185837173
num_examples: 834
download_size: 885325061
dataset_size: 940747197.376
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: mit
task_categories:
- text-to-speech
- automatic-speech-recognition
language:
- dv
tags:
- dhivehi
- divehi
- speech
- voice
pretty_name: kn_audio_dataset
size_categories:
- 1K<n<10K
Dhivehi Audio Dataset
This is a Dhivehi (Maldivian) speech synthesis dataset with audio recordings, text transcriptions, and phonetic annotations. All recordings are by one speaker.
Dataset Overview
This dataset provides 4,170 high-quality audio samples in Dhivehi.
Key Statistics
| Metric | Value |
|---|---|
| Total Audio Files | 4,170 |
| Total Duration | 5.87 hours (352.0 minutes) |
| Average Clip Length | 5.06 seconds |
| Total Words | 30,068 |
| Unique Phonemes | 14190 |
| Unique Characters | 62 |
Audio Specifications
- Sample Rate: 22050 Hz
- Channels: 1 (Mono/Stereo)
- Bit Depth: 16 bit
- Format: WAV (uncompressed)
Data Distribution
Duration Analysis
- Shortest clip: 1.18 seconds
- Longest clip: 19.08 seconds
- Standard deviation: 2.41 seconds
Text Characteristics
- Average sentence length: 65.7 characters
- Average words per sentence: 7.2
- Average phonemes per sentence: 7.2
- Sentence length range: 6 - 198 characters
Most Common Phonemes
| Phoneme | Count | Frequency |
|---|---|---|
ʋes̺ |
221 | 0.73% |
e |
212 | 0.70% |
eːn̪aː |
205 | 0.68% |
ahaɾeŋ |
170 | 0.56% |
ad̪i |
160 | 0.53% |
ʋaɾaʔ |
155 | 0.52% |
mi |
149 | 0.50% |
eiː |
146 | 0.49% |
n̪amaʋes̺ |
144 | 0.48% |
n̪uːŋ |
140 | 0.47% |
Common Voice 17.0 Comparison
This dataset was evaluated against the Dhivehi portion of Mozilla’s Common Voice 17.0 to assess overlap and uniqueness. The results are as follows:
| Metric | Value |
|---|---|
| Common Voice Sentences | 7,117 |
| This Dataset Sentences | 4,170 |
| Overlapping Sentences | 3,443 (82.6%) |
| Unique to This Dataset | 727 (17.4%) |
Although a substantial number of sentences are shared between the two datasets, each sentence in this dataset is recorded by a different speaker. This contributes to greater speaker diversity, making the dataset particularly suitable for training and evaluating speaker-independent models.
Key Insights
- 17.4% Unique Sentences: A notable portion of this dataset comprises sentences not present in Common Voice 17.0, contributing new linguistic content to the Dhivehi speech domain.
- Speaker and Quality Variation: Shared sentences offer a basis for evaluating speaker diversity and audio quality differences across datasets.
- Complementary Value: Serves as a valuable supplement to Common Voice 17.0 by providing additional recordings and speaker variability, enhancing the robustness of Dhivehi speech model training.
Example Sentence from Common Voice 17.0 Compared to This Dataset
| Common Voice 17.0 | This Dataset |
|---|---|
Use Cases
This dataset is suitable for:
- Text-to-Speech (TTS) synthesis - Training neural speech synthesis models
- Automatic Speech Recognition (ASR) - Dhivehi speech recognition systems
- Phonetic research - Analysis of Dhivehi phonology and pronunciation
- Language preservation - Digital archiving of Dhivehi speech patterns
- Cross-lingual studies - Comparative phonetic analysis
Loading the Dataset
Using 🤗 Datasets
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("alakxender/dhivehi-audio-kn")
# Access training split
train_data = dataset["train"]
# Example: Get first sample
sample = train_data[0]
print(f"Text: {sample['sentence']}")
print(f"Phonemes: {sample['phonemes']}")
# Audio is available in sample['audio']
Acknowledgments
Special thanks to @kudanai for providing the dataset used as the source. This dataset retains the same speaker, offering consistent voice characteristics across all recordings.