TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos
This corpus provides a valuable resource for researchers in speech science and technology, particularly for those working on articulatory-to-acoustic mapping and speech production modeling, by offering a large-scale, synchronized multimodal dataset.
This paper introduces the Tongue and Lips corpus (TaL), a multi-speaker dataset comprising 24 hours of synchronized ultrasound tongue imaging, audio, and lip videos. The corpus includes data from one professional voice talent (TaL1) and 81 non-professional speakers (TaL80), with approximately 13.5 hours of speech. The authors provide benchmark results for speech recognition, speech synthesis, and automatic ultrasound-to-audio synchronization.
We present the Tongue and Lips corpus (TaL), a multi-speaker corpus of audio, ultrasound tongue imaging, and lip videos. TaL consists of two parts: TaL1 is a set of six recording sessions of one professional voice talent, a male native speaker of English; TaL80 is a set of recording sessions of 81 native speakers of English without voice talent experience. Overall, the corpus contains 24 hours of parallel ultrasound, video, and audio data, of which approximately 13.5 hours are speech. This paper describes the corpus and presents benchmark results for the tasks of speech recognition, speech synthesis (articulatory-to-acoustic mapping), and automatic synchronisation of ultrasound to audio. The TaL corpus is publicly available under the CC BY-NC 4.0 license.