  In short video and live broadcasts, speech, singing voice, and background
music often overlap and obscure each other. This complexity creates
difficulties in structuring and recognizing the audio content, which may impair
subsequent ASR and music understanding applications. This paper proposes a
multi-task audio source separation (MTASS) based ASR model called JRSV, which
Jointly Recognizes Speech and singing Voices. Specifically, the MTASS module
separates the mixed audio into distinct speech and singing voice tracks while
removing background music. The CTC/attention hybrid recognition module
recognizes both tracks. Online distillation is proposed to improve the
robustness of recognition further. To evaluate the proposed methods, a
benchmark dataset is constructed and released. Experimental results demonstrate
that JRSV can significantly improve recognition accuracy on each track of the
mixed audio.
