Teochew-Wild: The First In-the-wild Teochew Dataset with Orthographic Annotations
This provides a foundational dataset for speech research in Teochew, a low-resource language, though it is incremental as it focuses on data creation rather than methodological innovation.
The authors tackled the lack of resources for the Teochew dialect by constructing Teochew-Wild, a 18.9-hour speech corpus with orthographic annotations, and validated its effectiveness in ASR and TTS tasks.
This paper reports the construction of the Teochew-Wild, a speech corpus of the Teochew dialect. The corpus includes 18.9 hours of in-the-wild Teochew speech data from multiple speakers, covering both formal and colloquial expressions, with precise orthographic and pinyin annotations. Additionally, we provide supplementary text processing tools and resources to propel research and applications in speech tasks for this low-resource language, such as automatic speech recognition (ASR) and text-to-speech (TTS). To the best of our knowledge, this is the first publicly available Teochew dataset with accurate orthographic annotations. We conduct experiments on the corpus, and the results validate its effectiveness in ASR and TTS tasks.