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The speaker extraction technique seeks to single out the voice of a targetspeaker from the interfering voices in a speech mixture. Typically an auxiliaryreference of the target speaker is used to form voluntary attention. Either apre-recorded utterance or a synchronized lip movement in a video clip can serveas the auxiliary reference. The use of visual cue is not only feasible, butalso effective due to its noise robustness, and becoming popular. However, itis difficult to guarantee that such parallel visual cue is always available inreal-world applications where visual occlusion or intermittent communicationcan occur. In this paper, we study the audio-visual speaker extractionalgorithms with intermittent visual cue. We propose a joint speaker extractionand visual embedding inpainting framework to explore the mutual benefits. Toencourage the interaction between the two tasks, they are performed alternatelywith an interlacing structure and optimized jointly. We also propose two typesof visual inpainting losses and study our proposed method with two types ofpopularly used visual embeddings. The experimental results show that weoutperform the baseline in terms of signal quality, perceptual quality, andintelligibility.

ImagineNET: Target Speaker Extraction with Intermittent Visual Cue through Embedding Inpainting