activity
20222026
most citedImproving the Robustness of DistilHuBERT to Unseen Noisy Conditions via Data Augmentation, Curriculum Learning, and Multi-Task Enhancement

3 citations · 6 across the 13 of their papers we have counts for

collaborators
Showing eess.ASShow all

13 papers · 1 filter

eess.AS2026

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…

eess.AS2026

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…

eess.AS2025

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.…

eess.AS2025

Improving Resource-Efficient Speech Enhancement via Neural Differentiable DSP Vocoder Refinement

Heitor R. Guimarães, Ke Tan, Juan Azcarreta +4

Deploying speech enhancement (SE) systems in wearable devices, such as smart glasses, is challenging due to the limited computational resources on the device. Although deep learnin…

eess.AS2025

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…

eess.AS2024

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,…