  There is growing interest in ASR systems that can recognize phones in a
language-independent fashion. There is additionally interest in building
language technologies for low-resource and endangered languages. However, there
is a paucity of realistic data that can be used to test such systems and
technologies. This paper presents a publicly available, phonetically
transcribed corpus of 2255 utterances (words and short phrases) in the
endangered Tangkhulic language East Tusom (no ISO 639-3 code), a Tibeto-Burman
language variety spoken mostly in India. Because the dataset is transcribed in
terms of phones, rather than phonemes, it is a better match for universal phone
recognition systems than many larger (phonemically transcribed) datasets. This
paper describes the dataset and the methodology used to produce it. It further
presents basic benchmarks of state-of-the-art universal phone recognition
systems on the dataset as baselines for future experiments.
