3 citations · 6 across the 7 of their papers we have counts for
9 papers
Acoustic Honeybee Queen-State Detection Under Unseen Conditions
Mahsa Abdollahi, Nico Coallier, Maxime Fraser Franco +1
Honeybee queen loss is a major threat to colony health, yet queen-status assessment remains largely manual and disruptive. Acoustic monitoring offers a non-invasive alternative by…
Improved Monitoring of Honey bee Colony Strength via Audio IoT Sensors, Modulation Tensorgrams and Recurrent Neural Networks
Mahsa Abdollahi, Yi Zhu, Heitor R. Guimarães +4
Honey bees (Apis mellifera) play a crucial role in agriculture and ecosystem stability as key pollinators of crops and wild plants. As such, monitoring hive strength remotely with…
BioME: A Resource-Efficient Bioacoustic Foundational Model for IoT Applications
Heitor R. Guimarães, Abhishek Tiwari, Mahsa Abdollahi +2
Passive acoustic monitoring has become a key strategy in biodiversity assessment, conservation, and behavioral ecology, especially as Internet-of-Things (IoT) devices enable contin…
AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors
Yi Zhu, Heitor R. Guimarães, Arthur Pimentel +1
With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on developing deepfake detection techniques.…
DiTSE: High-Fidelity Generative Speech Enhancement via Latent Diffusion Transformers
Heitor R. Guimarães, Jiaqi Su, Rithesh Kumar +2
Real-world speech recordings suffer from degradations such as background noise and reverberation. Speech enhancement aims to mitigate these issues by generating clean high-fidelity…
WavRx: a Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model
Yi Zhu, Tiago Falk
Speech is known to carry health-related attributes, which has emerged as a novel venue for remote and long-term health monitoring. However, existing models are usually tailored for…
UrBAN: Urban Beehive Acoustics and PheNotyping Dataset
Mahsa Abdollahi, Yi Zhu, Heitor R. Guimarães +4
In this paper, we present a multimodal dataset obtained from a honey bee colony in Montréal, Quebec, Canada, spanning the years of 2021 to 2022. This apiary comprised 10 beehives,…
MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees
Yi Zhu, Mahsa Abdollahi, Ségolène Maucourt +4
We present a longitudinal multi-sensor dataset collected from honey bee colonies (Apis mellifera) with rich phenotypic measurements. Data were continuously collected between May-20…
Characterizing the temporal dynamics of universal speech representations for generalizable deepfake detection
Yi Zhu, Saurabh Powar, Tiago H. Falk
Existing deepfake speech detection systems lack generalizability to unseen attacks (i.e., samples generated by generative algorithms not seen during training). Recent studies have…