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metadata
license: cc-by-nc-nd-4.0
task_categories:
  - automatic-speech-recognition
language:
  - ca
tags:
  - audio
  - speech
  - speech recognition
  - machine
  - machine learning
  - catalan
size_categories:
  - n<1K

🎧 Catalan Speech Dataset

The Catalan Speech Dataset is a high-quality speech audio dataset designed to provide reliable and diverse audio data for AI-driven voice technologies. It includes 140 hours of audio data distributed across 650 files, delivered in MP3 and WAV formats, with a total size of 245 MB. This well-structured audio dataset ensures balanced voice data, with 47% female and 53% male speakers, and a wide age distribution from 18 to 50+ years. The dataset language is Catalan, with speakers from Spain (Catalonia, Valencia, Balearic Islands), Andorra, France, and Italy (Alghero), making it a representative language speech dataset with strong regional and phonetic diversity.


πŸ”— Learn more:
https://speech-data.ai/datasets/catalan/


πŸš€ Use Cases

This Catalan speech dataset supports a wide range of AI applications, including speech recognition, voice assistant development, and natural language processing. The structured speech data enables efficient acoustic modeling, speaker identification, and scalable AI training workflows. It serves as a reliable speech recognition dataset for both research and production environments, ensuring consistent performance across dialects and recording conditions.


πŸ“Š Dataset Metadata

Field Value
πŸ“œ License CC BY-NC-ND 4.0
🎯 Task Categories Automatic Speech Recognition
🌍 Language Catalan (ca)
🏷️ Tags Audio, Speech, Speech Recognition, Machine, Machine Learning, Catalan
πŸ“¦ Size Category n < 1K

⭐ Key Value

The key value of this speech dataset lies in its geographic diversity, balanced demographics, and production-ready structure. It provides high-quality audio data that enhances the accuracy and robustness of voice-enabled AI systems. This voice dataset is particularly effective for building scalable multilingual solutions that require natural and diverse speech inputs.