Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification

2026-04-30

AI Summary

Traditional bioacoustic classification systems are constrained by a 16 kHz sampling rate, utilizing only the baseband (0–8 kHz) and neglecting the high-frequency—often ultrasonic—components prevalent in animal vocalizations. This work proposes a multi-band encoding framework that decomposes full-spectrum animal calls into multiple frequency bands and fuses them into a unified representation for classification. It presents the first systematic investigation into the efficacy of multi-band decomposition and fusion strategies for full-spectrum bioacoustic classification, revealing that specific encoder architectures can produce decorrelated band-wise embeddings that substantially enhance class separability. Experimental results across three datasets demonstrate that the proposed fused representation significantly outperforms both baseband-only and time-stretched baseline methods on two of the datasets.

Abstract

Animals hear and vocalize across frequency ranges that differ substantially from humans, often extending into the ultrasonic domain. Yet most computational bioacoustics systems rely on audio models pre-trained at 16 kHz, restricting their usable bandwidth to the 0-8 kHz baseband and discarding higher-frequency information present in many bioacoustic recordings. We investigate a multi-band encoding framework that decomposes the full spectrum of animal calls into band features and fuses them into a unified representation. Similarity analyses on models show that certain encoders produce decorrelated band embeddings that improve class separation after fusion. Classification experiments on three bioacoustic datasets using eight pre-trained models and five fusion strategies show that fused representations consistently outperform the baseband and time-expansion baselines on two datasets, showing the potential of multi-band methods for full-spectrum encoding of animal calls.

Problem

• bioacoustics
• full-spectrum
• multi-band encoding
• ultrasonic
• animal vocalization

Innovation

• multi-band encoding
• full-spectrum bioacoustics
• decorrelated embeddings
• adaptive fusion
• ultrasonic vocalization