3 accepted papers
The primary challenge in accent recognition lies in data scarcity due to the high diversity of accents, which make the collection of large-scale training data for each accent almost impossible in practice. To overcome this challenge, we propose a simple solution that leverages both continuous and di…
We introduce MIR-MLPop, a publicly available multilingual pop music dataset designed for automatic lyrics transcription and lyrics alignment in polyphonic music. The dataset comprises 90 pop music tracks in Mandarin, Cantonese, and Taiwanese Hokkien, with manually annotated time-aligned lyrics with…
This paper proposes a large-scale dataset for singing transcription, along with some methods for fine-tuning and validating its contents. The dataset is named MIR-ST500, which consists of more than 160,000 notes from 500 pop songs. To create this large-scale dataset, we set some labeling criteria an…