  In this paper, we introduce a new toolbox for constructing speech datasets
from long audio recording and raw reference texts. We develop tools for each
step of the speech dataset construction pipeline including data preprocessing,
audio-text alignment, data post-processing and filtering. The proposed pipeline
also supports human-in-the-loop to address text-audio mismatch issues and
remove samples that don't satisfy the quality requirements. We demonstrated the
toolbox efficiency by building the Russian LibriSpeech corpus (RuLS) from
LibriVox audiobooks. The toolbox is opne sourced in NeMo framework. The RuLS
corpus is released in OpenSLR.
