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We introduce HK-LegiCoST, a new three-way parallel corpus ofCantonese-English translations, containing 600+ hours of Cantonese audio, itsstandard traditional Chinese transcript, and English translation, segmented andaligned at the sentence level. We describe the notable challenges in corpuspreparation: segmentation, alignment of long audio recordings, andsentence-level alignment with non-verbatim transcripts. Such transcripts makethe corpus suitable for speech translation research when there are significantdifferences between the spoken and written forms of the source language. Due toits large size, we are able to demonstrate competitive speech translationbaselines on HK-LegiCoST and extend them to promising cross-corpus results onthe FLEURS Cantonese subset. These results deliver insights into speechrecognition and translation research in languages for which non-verbatim or``noisy'' transcription is common due to various factors, including vernacularand dialectal speech.

HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation