# Binaural Target Speaker Extraction using Individualized HRTF

Source: [Binaural Target Speaker Extraction using Individualized HRTF](<https://www.sota2.com/research/paper/68fa7b4a1e209131cea87913>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:00:04.574Z

Authors: Yoav Ellinson, Sharon Gannot

Published: 2025-07-25T15:20:49.000Z

## Abstract

In this work, we address the problem of binaural target-speaker extraction in the presence of multiple simultane-ous talkers. We propose a novel approach that leverages the individual listener's Head-Related Transfer Function (HRTF) to isolate the target speaker. The proposed method is speaker-independent, as it does not rely on speaker embeddings. We employ a fully complex-valued neural network that operates directly on the complex-valued Short-Time Fourier transform (STFT) of the mixed audio signals, and compare it to a Real-Imaginary (RI)-based neural network, demonstrating the advantages of the former. We first evaluate the method in an anechoic, noise-free scenario, achieving excellent extraction performance while preserving the binaural cues of the target signal. We then extend the evaluation to reverberant conditions. Our method proves robust, maintaining speech clarity and source directionality while simultaneously reducing reverberation. A comparative analysis with existing binaural Target Speaker Extraction (TSE) methods shows that the proposed approach achieves performance comparable to state-of-the-art techniques in terms of noise reduction and perceptual quality, while providing a clear advantage in preserving binaural cues. Demo-page: https://bi-ctse-hrtf.github.io

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Binaural Target Speech Extraction on WSJ0](<https://www.sota2.com/research/sota/binaural-target-speech-extraction-on-wsj0.md>): Binaural Target Speech Extraction; WSJ0; DNSMOS Overall: 3.18.

- [Binaural Target Speech Extraction on WSJ0 Reverb](<https://www.sota2.com/research/sota/binaural-target-speech-extraction-on-wsj0-reverb.md>): Binaural Target Speech Extraction; WSJ0 Reverb; DNSMOS-OVRL: 3.03.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2507.19369>)

[PDF](<https://arxiv.org/pdf/2507.19369.pdf>)