Listening for "You": Enhancing Speech Image Retrieval via Target Speaker Extraction

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Yang, Wenhao, Wei, Jianguo, Lu, Wenhuan, Song, Xinyue, Yue, Xianghu
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918139337375744
author Yang, Wenhao
Wei, Jianguo
Lu, Wenhuan
Song, Xinyue
Yue, Xianghu
author_facet Yang, Wenhao
Wei, Jianguo
Lu, Wenhuan
Song, Xinyue
Yue, Xianghu
contents Image retrieval using spoken language cues has emerged as a promising direction in multimodal perception, yet leveraging speech in multi-speaker scenarios remains challenging. We propose a novel Target Speaker Speech-Image Retrieval task and a framework that learns the relationship between images and multi-speaker speech signals in the presence of a target speaker. Our method integrates pre-trained self-supervised audio encoders with vision models via target speaker-aware contrastive learning, conditioned on a Target Speaker Extraction and Retrieval module. This enables the system to extract spoken commands from the target speaker and align them with corresponding images. Experiments on SpokenCOCO2Mix and SpokenCOCO3Mix show that TSRE significantly outperforms existing methods, achieving 36.3% and 29.9% Recall@1 in 2 and 3 speaker scenarios, respectively - substantial improvements over single speaker baselines and state-of-the-art models. Our approach demonstrates potential for real-world deployment in assistive robotics and multimodal interaction systems.
format Preprint
id arxiv_https___arxiv_org_abs_2509_09306
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Listening for "You": Enhancing Speech Image Retrieval via Target Speaker Extraction
Yang, Wenhao
Wei, Jianguo
Lu, Wenhuan
Song, Xinyue
Yue, Xianghu
Audio and Speech Processing
Image and Video Processing
Image retrieval using spoken language cues has emerged as a promising direction in multimodal perception, yet leveraging speech in multi-speaker scenarios remains challenging. We propose a novel Target Speaker Speech-Image Retrieval task and a framework that learns the relationship between images and multi-speaker speech signals in the presence of a target speaker. Our method integrates pre-trained self-supervised audio encoders with vision models via target speaker-aware contrastive learning, conditioned on a Target Speaker Extraction and Retrieval module. This enables the system to extract spoken commands from the target speaker and align them with corresponding images. Experiments on SpokenCOCO2Mix and SpokenCOCO3Mix show that TSRE significantly outperforms existing methods, achieving 36.3% and 29.9% Recall@1 in 2 and 3 speaker scenarios, respectively - substantial improvements over single speaker baselines and state-of-the-art models. Our approach demonstrates potential for real-world deployment in assistive robotics and multimodal interaction systems.
title Listening for "You": Enhancing Speech Image Retrieval via Target Speaker Extraction
topic Audio and Speech Processing
Image and Video Processing
url https://arxiv.org/abs/2509.09306