A small Griko-Italian speech translation corpus
This work addresses the need for accessible data in computational language documentation for endangered languages like Griko, though it is incremental as it extends an existing corpus.
The authors tackled the problem of limited resources for computational research on the endangered Griko language by creating a small parallel speech translation corpus with 330 utterances, and they demonstrated its utility through baseline results for speech-to-translation alignment and unsupervised word discovery tasks.
This paper presents an extension to a very low-resource parallel corpus collected in an endangered language, Griko, making it useful for computational research. The corpus consists of 330 utterances (about 20 minutes of speech) which have been transcribed and translated in Italian, with annotations for word-level speech-to-transcription and speech-to-translation alignments. The corpus also includes morphosyntactic tags and word-level glosses. Applying an automatic unit discovery method, pseudo-phones were also generated. We detail how the corpus was collected, cleaned and processed, and we illustrate its use on zero-resource tasks by presenting some baseline results for the task of speech-to-translation alignment and unsupervised word discovery. The dataset is available online, aiming to encourage replicability and diversity in computational language documentation experiments.