  Thousands of the world's languages are in danger of extinction--a tremendous
threat to cultural identities and human language diversity. Interlinear Glossed
Text (IGT) is a form of linguistic annotation that can support documentation
and resource creation for these languages' communities. IGT typically consists
of (1) transcriptions, (2) morphological segmentation, (3) glosses, and (4)
free translations to a majority language. We propose Wav2Gloss: a task in which
these four annotation components are extracted automatically from speech, and
introduce the first dataset to this end, Fieldwork: a corpus of speech with all
these annotations, derived from the work of field linguists, covering 37
languages, with standard formatting, and train/dev/test splits. We provide
various baselines to lay the groundwork for future research on IGT generation
from speech, such as end-to-end versus cascaded, monolingual versus
multilingual, and single-task versus multi-task approaches.
