ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development

TL;DR

The paper introduces ivrit.ai, a large, accessible Hebrew speech dataset with diverse speakers and formats, designed to advance Hebrew ASR technology and AI applications.

Contribution

It provides the first extensive, legally accessible Hebrew speech dataset with multiple data formats, supporting diverse research and development needs.

Findings

Over 3,300 hours of speech data collected

Contains data from over a thousand speakers

Available in raw, processed, and transcribed forms

Abstract

We introduce "ivrit.ai", a comprehensive Hebrew speech dataset, addressing the distinct lack of extensive, high-quality resources for advancing Automated Speech Recognition (ASR) technology in Hebrew. With over 3,300 speech hours and a over a thousand diverse speakers, ivrit.ai offers a substantial compilation of Hebrew speech across various contexts. It is delivered in three forms to cater to varying research needs: raw unprocessed audio; data post-Voice Activity Detection, and partially transcribed data. The dataset stands out for its legal accessibility, permitting use at no cost, thereby serving as a crucial resource for researchers, developers, and commercial entities. ivrit.ai opens up numerous applications, offering vast potential to enhance AI capabilities in Hebrew. Future efforts aim to expand ivrit.ai further, thereby advancing Hebrew's standing in AI research and technology.