Rule-embedded network for audio-visual voice activity detection in live musical video streams

Paper

Please see here (https://arxiv.org/abs/2010.14168).

Code

Please see here.

Open dataset MAVC100

For detailed information and download of the MAVC100, please see here.

Demos of the detection results

Here are the detection results based on rule-embedded audio-visual VAD network in the paper.
The font on the top left of the video shows the activity of the anchor at the current moment. The anchor speaks, it shows speech; the anchor sings, it shows singing; the anchor has no action and there is sound in the background, it shows silence; otherwise it shows others.
(For the purpose of protecting privacy, we covered the face of the anchor in the video clip and interfered with her or his voice.)


The proposed rule-embedded AV-VAD network

The left part is audio branch (red words) that tries to learn the high-level acoustic features of target events in audio level, and right part is image branch (blue words) attempts to judge whether the anchor is vocalizing using visual information. The bottom part is the Audio-Visual branch (purple italics), which aims to fuse the bi-modal representations to determine the probability of target events of this paper.

The original output of the rule-embedded AV-VAD network

In subgraph (a), the red, blue, gray and green lines denote the probability of Singing, Speech, Others and Silence in audio, respectively.
In subgraph (b), the gray and black lines denote the probability of vocalizing and non-vocalizing, respectively.
In subgraph (c), the red, blue and gray lines denote the probability of target Singing, Speech and Others, and the other remaining part is Silence.

Citation

Please feel free to use the open dataset MAVC100 and consider citing our paper as

Bibtex

@inproceedings{icassp2021_hou, author = {Yuanbo Hou and Yi Deng and Bilei Zhu and Zejun Ma and Dick Botteldooren}, title = {Rule-embedded network for audio-visual voice activity detection in live musical video streams}, booktitle = {{IEEE} International Conference on Acoustics, Speech and Signal Processing, {ICASSP} 2021}, publisher = {{IEEE}}, year = {2021} }