{"ID":2862726,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.26133","arxiv_id":"2509.26133","title":"Zimtohrli: An Efficient Psychoacoustic Audio Similarity Metric","abstract":"This paper introduces Zimtohrli, a novel, full-reference audio similarity metric designed for efficient and perceptually accurate quality assessment. In an era dominated by computationally intensive deep learning models and proprietary legacy standards, there is a pressing need for an interpretable, psychoacoustically-grounded metric that balances performance with practicality. Zimtohrli addresses this gap by combining a 128-bin gammatone filterbank front-end, which models the frequency resolution of the cochlea, with a unique non-linear resonator model that mimics the human eardrum's response to acoustic stimuli. Similarity is computed by comparing perceptually-mapped spectrograms using modified Dynamic Time Warping (DTW) and Neurogram Similarity Index Measure (NSIM) algorithms, which incorporate novel non-linearities to better align with human judgment. Zimtohrli achieves superior performance to the baseline open-source ViSQOL metric, and significantly narrows the performance gap with the latest commercial POLQA metric. It offers a compelling balance of perceptual relevance and computational efficiency, positioning it as a strong alternative for modern audio engineering applications, from codec development to the evaluation of generative audio systems.","short_abstract":"This paper introduces Zimtohrli, a novel, full-reference audio similarity metric designed for efficient and perceptually accurate quality assessment. In an era dominated by computationally intensive deep learning models and proprietary legacy standards, there is a pressing need for an interpretable, psychoacoustically-...","url_abs":"https://arxiv.org/abs/2509.26133","url_pdf":"https://arxiv.org/pdf/2509.26133v1","authors":"[\"Jyrki Alakuijala\",\"Martin Bruse\",\"Sami Boukortt\",\"Jozef Marus Coldenhoff\",\"Milos Cernak\"]","published":"2025-09-30T11:54:44Z","proceeding":"eess.AS","tasks":"[\"eess.AS\"]","methods":"[]","has_code":false}