Abstract
With the sharp booming of online live streaming platforms, some anchors seek profits and accumulate popularity by mixing inappropriate content into live programs. After being blacklisted, these anchors even forged their identities to change the platform to continue live, causing great harm to the network environment. Therefore, we propose an anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit (GRU) for anchor identification of live platform. First, the speech of the anchor is extracted from the live streaming by using voice activation detection (VAD) and speech separation. Then, the feature sequence of anchor voiceprint is generated from the speech waveform with the self-attention network RawNet-SA. Finally, the feature sequence of anchor voiceprint is aggregated by GRU to transform into a deep voiceprint feature vector for anchor recognition. Experiments are conducted on the VoxCeleb, CN-Celeb, and MUSAN dataset, and the competitive results demonstrate that our method can effectively recognize the anchor voiceprint in video streaming.
Highlights
With the substantial advances in computing technology, live video streaming is becoming increasingly popular
The feature sequence of anchor voiceprint is aggregated by gated recurrent unit (GRU) and transformed into deep voiceprint feature vector for anchor recognition
The feature sequence of anchor voiceprint is aggregated by GRU to transform into a deep voiceprint feature vector for anchor recognition
Summary
With the substantial advances in computing technology, live video streaming is becoming increasingly popular. Due to the low employment threshold and acute competition of anchors, there are some issues in the online live streaming industry, such as unreasonable content ecology and uneven anchor quality. For seeking profits and accumulating popularity, some anchors mix inappropriate content into live programs. These offending anchors are usually found and banned after a period of time. They can still live by registering their subaccounts as other anchors or occupying the rooms of other anchors after being blacklisted, which has caused great harm to the network environment. It is indispensable to apply intelligent analysis techniques to identify anchors according to the specific characteristics
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