  While the Turkish language is listed among low-resource languages, literature
on Turkish automatic speech recognition (ASR) is relatively old. In this
report, we present our findings on Turkish ASR with speech representation
learning using HUBERT. We investigate pre-training HUBERT for Turkish with
large-scale data curated from online resources. We pre-train our model using
6,500 hours of speech data from YouTube. The results show that the models are
not ready for commercial use since they are not robust against disturbances
that typically occur in real-world settings such as variations in accents,
slang, background noise and interference. We analyze typical errors and the
limitations of the models for use in commercial settings.
