A speaker extraction algorithm seeks to extract the speech of a target speaker from a multi-
talker speech mixture when given a cue that represents the target speaker, such as a pre …

The biological neurons use precise spike times, in addition to the spike firing rate, to
communicate with each other. The time-to-first-spike (TTFS) coding is inspired by such …

Speaker embeddings have become the most popular feature representation in speaker
verification. Improving the robustness of speaker embedding extraction systems is a crucial …

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 …

Speech separation seeks to separate individual speech signals from a speech mixture.
Typically, most separation models are trained on synthetic data due to the unavailability of …

Speaker extraction and diarization are two enabling techniques for real-world speech
applications. Speaker extraction aims to extract a target speaker's voice from a speech …

In this paper, we propose a speaker verification method by an Attentive Multi-scale
Convolutional Recurrent Network (AMCRN). The proposed AMCRN can acquire both local …

Existing methods for few-shot speaker identification (FSSI) obtain high accuracy, but their
computational complexities and model sizes need to be reduced for lightweight applications …

In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding
extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric …

Target speaker extraction (TSE) aims to isolate individual speaker voices from complex
speech environments. The effectiveness of TSE systems is often compromised when the …