Positive Transfer of the Whisper Speech Transformer to Human and Animal Voice Activity Detection
Abstract
This paper introduces WhisperSeg, utilizing the Whisper Transformer pre-trained for Automatic Speech Recognition (ASR) for human and animal Voice Activity Detection (VAD). Contrary to traditional methods that detect human voice or animal vocalizations from a short audio frame and rely on careful threshold selection, WhisperSeg processes entire spectrograms of long audio and generates plain text representations of onset, offset, and type of voice activity. Processing a longer audio context with a larger network greatly improves detection accuracy from few labeled examples. We further demonstrate a positive transfer of detection performance to new animal species, making our approach viable in the data-scarce multi-species setting.1
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Automated speech detection in eco-acoustic data enables privacy protection and human disturbance quantification
Benjamin Cretois, Carolyn M. Rosten, Sarab S. Sethi·Methods in Ecology and EvolutionPeer-reviewed·Oct 18, 2022
- TweetyBERT: Automated parsing of birdsong through self-supervised machine learning.
George Vengrovski, Miranda Hulsey-Vincent, … Timothy J. Gardner·PatternsPeer-reviewed·Mar 3, 2026
- SqueakOut: Autoencoder-based segmentation of mouse ultrasonic vocalizations
Gustavo Moreira Tavares Santana, Marcelo O. Dietrich·bioRxiv·Apr 19, 2024
- A Vision-Language Model as a Teacher for Bird Vocalization Detection
George Vengrovski, Timothy J. Gardner·bioRxiv·Sep 25, 2026
- Bioacoustic Event Detection with Self-SupervisedContrastive Learning
P. C. Bermant, L. Brickson, A. J. Titus·bioRxiv·Oct 12, 2022
- SongExplorer: A deep learning workflow for discovery and segmentation of animal acoustic communication signals
B. J. Arthur, Y. Ding, … D. Stern·bioRxiv·Mar 26, 2021