India is home to a multitude of languages of which 22 languages are
recognised by the Indian Constitution as official. Building speech based
applications for the Indian population is a difficult problem owing to limited
data and the number of languages and accents to accommodate. To encourage the
language technology community to build speech based applications in Indian
languages, we are open sourcing SPRING-INX data which has about 2000 hours of
legally sourced and manually transcribed speech data for ASR system building in
Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi
and Tamil. This endeavor is by SPRING Lab , Indian Institute of Technology
Madras and is a part of National Language Translation Mission (NLTM), funded by
the Indian Ministry of Electronics and Information Technology (MeitY),
Government of India. We describe the data collection and data cleaning process
along with the data statistics in this paper.

印度拥有多种语言，其中有 22 种语言被印度宪法正式认可。为印度人口构建基于语音的应用程序是一个困难的问题，因为数据有限且需要适应不同的语言和口音。为了鼓励语言技术社区在印度语言中构建基于语音的应用程序，我们向开源社区提供了 SPRING-INX 数据，其中包括 2000 小时的合法获取和手动转录的语音数据，用于搭建 ASR 系统。这个努力是由印度理工学院马德拉斯分校的 SPRING 实验室和由印度电子与信息技术部（MeitY）资助的全国语种翻译计划的一部分。本文介绍了数据收集和数据清洗的过程，并提供了数据统计。