Speech-data/Polish-Speech-Dataset
π§ Polish Speech Dataset The Polish Speech Dataset is a high-quality speech audio dataset designed to support advanced AI and machine learning systems with structured and diverse audio data. It includes 121 hours of recorded speech data across 688 files, provided in MP3 and WAV formats, with a total size of 207 MB. This carefully curated audio dataset ensures balanced and representative voice data, with 51% female and 49% male speakers, and age distribution spanning from 18 toβ¦ See the full description on the dataset page: https://huggingface.co/datasets/Speech-data/Polish-Speech-Dataset.
π§ Polish Speech Dataset
The Polish Speech Dataset is a high-quality speech audio dataset designed to support advanced AI and machine learning systems with structured and diverse audio data. It includes 121 hours of recorded speech data across 688 files, provided in MP3 and WAV formats, with a total size of 207 MB. This carefully curated audio dataset ensures balanced and representative voice data, with 51% female and 49% male speakers, and age distribution spanning from 18 to 50+ years. The dataset language is Polish, with recordings collected across Poland and several international regions including the USA, UK, and Germany, enabling strong accent and dialect coverage for robust model training.
π Learn more: https://speech-data.ai/datasets/polish/
π Use Cases
This Polish speech dataset is suitable for a wide range of AI applications, including speech recognition, voice assistant development, and natural language processing. The structured speech data enables acoustic modeling, speaker identification, and multilingual system training. As a reliable speech recognition dataset, it supports both research and production environments that require high-quality speech audio dataset inputs. Its geographic diversity makes it especially valuable for building systems capable of handling real-world variability in pronunciation and accent.
π Dataset Metadata
β Key Value
The key value of this voice dataset lies in its demographic balance, geographic diversity, and production-ready structure. It delivers high-quality audio data that improves model robustness and generalization across accents and speaking styles. This speech dataset provides a strong foundation for scalable, accurate, and multilingual voice AI systems.
