  Speaker extraction aims to extract the target speaker's voice from a
multi-talker speech mixture given an auxiliary reference utterance. Recent
studies show that speaker extraction benefits from the location or direction of
the target speaker. However, these studies assume that the target speaker's
location is known in advance or detected by an extra visual cue, e.g., face
image or video. In this paper, we propose an end-to-end localized target
speaker extraction on pure speech cues, that is called L-SpEx. Specifically, we
design a speaker localizer driven by the target speaker's embedding to extract
the spatial features, including direction-of-arrival (DOA) of the target
speaker and beamforming output. Then, the spatial cues and target speaker's
embedding are both used to form a top-down auditory attention to the target
speaker. Experiments on the multi-channel reverberant dataset called
MC-Libri2Mix show that our L-SpEx approach significantly outperforms the
baseline system.
