SQuTR: A Robustness Benchmark for Spoken Query to Text Retrieval under Acoustic Noise

ArXi:2602.12783v2 Announce Type: replace-cross Spoken query retrieval is an important interaction mode in modern information retrieval. However, existing evaluation datasets are often limited to simple queries under constrained noise conditions, making them inadequate for assessing the robustness of spoken query retrieval systems under complex acoustic perturbations. To address this limitation, we present SQuTR, a robustness benchmark for spoken query retrieval that includes a large-scale dataset and a unified evaluation protocol.