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metadata
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

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