Datasets:
language:
- bn
pretty_name: Bengali Telecom Customer Care Synthetic Speech
tags:
- audio
- speech
- bengali
- bangla
- customer-care
- telecom
- telecommunication
- telco
- synthetic
- tts
- stt
- text-to-speech
- speech-to-text
- automatic-speech-recognition
task_categories:
- text-to-speech
- speech-to-text
- automatic-speech-recognition
license: cc-by-4.0
Bengali Telecom Customer Care Synthetic Speech Dataset
Dataset Description
This dataset contains synthetic Bengali speech generated from telecom and customer-care style text prompts.
The dataset is intended for experiments with:
- Bengali ASR/STT
- Bengali TTS
- Speech-to-text preprocessing
- Telecom/customer-care domain adaptation
- Synthetic speech research
Important Disclosure
This is a synthetic speech dataset generated using a TTS system.
It does not contain real customer-care recordings, real customer conversations, or real user audio.
Dataset Size
Total examples: 10000
Approximate total duration: 26.82 hours
Sample rate: 24000 Hz
Splits:
| Split | Examples |
|---|---|
| Train | 9000 |
| Validation | 500 |
| Test | 500 |
Dataset Structure
bengali-telecom-customer-care-speech/
└── data/
├── train/
│ ├── metadata.jsonl
│ └── audios/
├── validation/
│ ├── metadata.jsonl
│ └── audios/
└── test/
├── metadata.jsonl
└── audios/
Each metadata row contains:
{
"file_name": "audios/example.wav",
"text": "Original Bengali text.",
"text_normalized": "Normalized Bengali text.",
"language": "bn",
"is_synthetic": true,
"sample_rate": 24000,
"duration_sec": 5.32
}
Field Descriptions
| Field | Description |
|---|---|
file_name |
Relative path to the audio file |
text |
Original Bengali text used for TTS generation |
text_normalized |
Normalized Bengali text suitable for ASR/STT training |
language |
Language code, bn for Bengali |
is_synthetic |
Whether the sample is synthetic |
sample_rate |
Audio sample rate |
duration_sec |
Audio duration in seconds |
Intended Use
For TTS training, use:
text -> audio
For ASR/STT training, use:
audio -> text_normalized
Limitations
Because this dataset is synthetic, models trained only on this dataset may not fully generalize to real-world speech, noisy phone calls, spontaneous conversation, different microphones, real accents, or background noise.
For production-quality ASR or TTS, this dataset should ideally be combined with real human-recorded Bengali speech.
License
License: cc-by-4.0
Prepared By
- Kawshik Kumar Paul
Dept of CSE, BUET
kawshikbuet17@gmail.com - Nafiul Alam Fuji
Dept of CSE, BUET
nafiul.fuji@gmail.com