most citedMSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

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,…

eess.AS2024

An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task Learning

Heitor R. Guimarães, Arthur Pimentel, Anderson R. Avila +3

Self-supervised speech representation learning enables the extraction of meaningful features from raw waveforms. These features can then be efficiently used across multiple downstr…

eess.AS20232 cited

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…

eess.AS2023

On the Impact of Quantization and Pruning of Self-Supervised Speech Models for Downstream Speech Recognition Tasks "In-the-Wild''

Arthur Pimentel, Heitor Guimarães, Anderson R. Avila +2

Recent advances with self-supervised learning have allowed speech recognition systems to achieve state-of-the-art (SOTA) word error rates (WER) while requiring only a fraction of t…

eess.AS2023

VIC-KD: Variance-Invariance-Covariance Knowledge Distillation to Make Keyword Spotting More Robust Against Adversarial Attacks

Heitor R. Guimarães, Arthur Pimentel, Anderson Avila +1

Keyword spotting (KWS) refers to the task of identifying a set of predefined words in audio streams. With the advances seen recently with deep neural networks, it has become a popu…

eess.AS20231 cited

On the Transferability of Whisper-based Representations for "In-the-Wild" Cross-Task Downstream Speech Applications

Vamsikrishna Chemudupati, Marzieh Tahaei, Heitor Guimaraes +5

Large self-supervised pre-trained speech models have achieved remarkable success across various speech-processing tasks. The self-supervised training of these models leads to unive…