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We introduce the Merkel Podcast Corpus, an audio-visual-text corpus in Germancollected from 16 years of (almost) weekly Internet podcasts of former Germanchancellor Angela Merkel. To the best of our knowledge, this is the firstsingle speaker corpus in the German language consisting of audio, visual andtext modalities of comparable size and temporal extent. We describe the methodsused with which we have collected and edited the data which involvesdownloading the videos, transcripts and other metadata, forced alignment,performing active speaker recognition and face detection to finally curate thesingle speaker dataset consisting of utterances spoken by Angela Merkel. Theproposed pipeline is general and can be used to curate other datasets ofsimilar nature, such as talk show contents. Through various statisticalanalyses and applications of the dataset in talking face generation and TTS, weshow the utility of the dataset. We argue that it is a valuable contribution tothe research community, in particular, due to its realistic and challengingmaterial at the boundary between prepared and spontaneous speech.

Merkel Podcast Corpus: A Multimodal Dataset Compiled from 16 Years of Angela Merkel's Weekly Video Podcasts