Datasets:
license: cc-by-nc-nd-4.0
task_categories:
- automatic-speech-recognition
language:
- id
tags:
- audio
- speech
- speech recognition
- Indonesian
- machine
- machine learning
size_categories:
- n<1K
🎧 Indonesian Speech Dataset
The Indonesian Speech Dataset is a high-quality speech audio dataset designed to deliver structured and scalable audio data for AI-powered voice systems. It contains 162 hours of audio data across 821 files, provided in MP3 and WAV formats, with a total size of 210 MB. This well-curated audio dataset ensures balanced and representative voice data, with 51% female and 49% male speakers, and a broad age distribution from 18 to 50+ years. The dataset language is Indonesian, making it a reliable language speech dataset for modeling real-world speech patterns in one of the most widely spoken languages in Southeast Asia.
🔗 Learn more:
https://speech-data.ai/datasets/indonesian/
🚀 Use Cases
This Indonesian speech dataset is designed for a wide range of AI applications, including speech recognition, voice assistant development, and natural language processing. The structured speech data supports acoustic modeling, speaker identification, and scalable machine learning pipelines. It also enables the development of multilingual systems that depend on high-quality speech audio dataset resources. As a robust speech recognition dataset, it is suitable for both research and production environments where consistent and diverse audio data is required.
📊 Dataset Metadata
| Field | Value |
|---|---|
| 📜 License | CC BY-NC-ND 4.0 |
| 🎯 Task Categories | Automatic Speech Recognition |
| 🌍 Language | Indonesian (id) |
| 🏷️ Tags | Audio, Speech, Speech Recognition, Indonesian, Machine, Machine Learning |
| 📦 Size Category | n < 1K |
⭐ Key Value
The key value of this voice dataset lies in its structured composition, demographic diversity, and production-ready quality. It provides high-quality audio data that improves model accuracy and generalization across real-world scenarios. This speech dataset is ideal for building scalable, high-performance voice-enabled AI systems.