Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2609.08422

Beyond Localisation Accuracy: Sensorimotor Effects of HRTF Individualisation

Fulvio Missoni·Katarina C. Poole·Tim Murray-Browne·Andrea Canessa·Lorenzo Picinali
View original source ↗Read source document ↗Export metadata ↓

Abstract

Everyday listening requires the brain to integrate cues from the body, environment, other senses, and movement, continuously translating auditory information into action. Yet HRTF individualisation is still commonly assessed through localisation accuracy, which may not fully capture its effects on this sensorimotor process. Here, we investigate whether these effects can instead be revealed through behaviour in a more ecologically valid listening task. We used an aurally guided visual search paradigm in which listeners located a visual target using a co-located virtual sound while moving freely, comparing individualised and non-individualised HRTFs under anechoic and reverberant conditions. Performance was assessed through response times and measures of movement organisation. In anechoic conditions, individualised HRTFs produced faster responses than non-individualised HRTFs, with an average reduction of approximately 200ms and the clearest benefit for front-back source locations. This advantage was expressed primarily in movement initiation, whereas overall movement extent was only weakly affected. Under reverberant conditions, HRTF-dependent differences disappeared. These results suggest that HRTF individualisation can influence how listeners plan and initiate orienting actions even when differences in conventional localisation outcomes are limited. Assessing sensorimotor behaviour alongside localisation performance may therefore provide a more sensitive and ecologically relevant account of the perceptual benefits of HRTF individualisation.

Explore related subjects

eess.AS

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fulvio Missoni, Katarina C. Poole, Tim Murray-Browne, Andrea Canessa, Lorenzo Picinali. 2026-09-08. Beyond Localisation Accuracy: Sensorimotor Effects of HRTF Individualisation. https://arxiv.org/abs/2609.08422

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Revisiting Lexicon Evaluation in Unsupervised Word Discovery

Building a lexicon from discovered word-like units is a central goal in zero-resource speech processing. But do our evaluations provide a trustworthy indication of lexicon quality? A common metric, normalized edit distance, averages the phoneme edit distances between discovered units in each cluster. We show that this metric has an inherent bias toward the quality of large clusters, inhibiting fair evaluation. Moreover, it ignores how well true classes are distributed across clusters. Based on established theory in clustering literature, we propose two metrics that address these shortcomings: a modified metric that weighs cluster size when assessing within-cluster consistency, and an inverse metric that assesses how true words are spread across clusters. Through experiments on synthetic and real-world lexicons, we demonstrate that combined, these metrics are: (1) more closely correlated with how similar a lexicon is to the ground-truth distribution, and (2) more robust to biases that skew lexicon evaluations.

eess.AS↗
arXiv2026

AURA: Uncertainty-Routed Activation Editing for Acoustic Grounding in Speech Foundation Models

Attention encoder-decoder (AED) Speech Foundation Models achieve strong ASR performance but can generate acoustically unsupported text when inputs contain no speech, weak acoustic evidence, or unreliable transcription. We propose AURA: Activation-editing with Uncertainty-Routed Adaptation, an ultra-efficient representation-editing method that freezes the pretrained model and applies sparse scale-and-shift edits to decoder cross-attention heads. AURA dynamically routes edits using cross-attention uncertainty features that capture over-concentration, diffuse attention, and abrupt frame shifts. We evaluate AURA on four datasets spanning non-speech hallucination and speech grounding stressors, including imperfect-label child speech, imperfect-label adult speech, and disfluent speech. On non-speech audio, AURA reduces hallucination rate from 89.18% to 1.94% without prior hallucination-head identification. On imperfect-label corpora, AURA approaches LoRA WER while using roughly 500x fewer trainable parameters. Sensitivity analysis and qualitative cross-attention examples are consistent with AURA's uncertainty-routed editing behavior, supporting dynamic activation editing as a practical path for grounding AED speech models.

eess.AS↗
arXiv2026

The design of an optomechanical microphone using a photonic waveguide interferometer

We present an optomechanical microphone based on a diaphragm-integrated photonic waveguide Mach-Zehnder interferometer. Acoustic pressure deforms the MEMS diaphragm, inducing strain in the sensing waveguide and changing its optical path length. We analytically evaluate the optical and mechanical transduction mechanisms and key figures of merit, including signal-to-noise ratio, dynamic range, acoustic overload pressure, and minimum detectable pressure. Two design cases are considered: a MEMS microphone and a measurement microphone. The results indicate competitive performance but no substantial overall advantage over state-of-the-art microphones in conventional applications. The architecture may nevertheless offer advantages for high-temperature and other harsh-environment sensing applications.

eess.AS↗