activity
20192021
most citedBlind Mask to Improve Intelligibility of Non-Stationary Noisy Speech

10 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2021

Noisy Speech Based Temporal Decomposition to Improve Fundamental Frequency Estimation

A. Queiroz, R. Coelho

This paper introduces a novel method to separate noisy speech into low or high frequency frames, in order to improve fundamental frequency (F0) estimation accuracy. In this proposa…

eess.AS2020★ 10 cited

Blind Mask to Improve Intelligibility of Non-Stationary Noisy Speech

F. Farias, R. Coelho

This letter proposes a novel blind acoustic mask (BAM) designed to adaptively detect noise components and preserve target speech segments in time-domain. A robust standard deviatio…

eess.AS2019★ 5 cited

Adaptive Reverberation Absorption using Non-stationary Masking Components Detection for Intelligibility Improvement

G. Zucatelli, R. Coelho

This letter proposes a new time domain absorption approach designed to reduce masking components of speech signals under noisy-reverberant conditions. In this method, the non-stati…

eess.AS2019★ 1 cited

Impulsive Noise Detection for Intelligibility and Quality Improvement of Speech Enhancement Methods Applied in Time-Domain

C. Medina, R. Coelho

This letter introduces a novel speech enhancement method in the Hilbert-Huang Transform domain to mitigate the effects of acoustic impulsive noises. The estimation and selection of…

eess.AS2019

Effective Acoustic Energy Sensing Exploitation for Target Sources Localization in Urban Acoustic Scenes

M. Alves, R. Coelho, E. Dranka

This letter proposes a new approach to improve the accuracy of the Energy-based source localization methods in urban acoustic scenes. The proposed acoustic energy sensing flow esti…

eess.AS2019

Objective Human Affective Vocal Expression Detection and Automatic Classification with Stochastic Models and Learning Systems

V. Vieira, R. Coelho, F. Assis

This paper presents a widespread analysis of affective vocal expression classification systems. In this study, state-of-the-art acoustic features are compared to two novel affectiv…