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Publicações

Publicações por CTM

2025

A Review of Voicing Decision in Whispered Speech: From Rules to Machine Learning

Autores
da Silva, JMPP; Duarte Nunes, G; Ferreira, A;

Publicação

Abstract

2025

Neural network models for whisper to normal speech conversion

Autores
Yamamura, F; Scalassara, R; Oliveira, A; Ferreira, JS;

Publicação
U.Porto Journal of Engineering

Abstract
Whispers are common and essential for secondary communication. Nonetheless, individuals with aphonia, including laryngectomees, rely on whispers as their primary means of communication. Due to the distinct features between whispered and regular speech, debates have emerged in the field of speech recognition, highlighting the challenge of effectively converting between them. This study investigates the characteristics of whispered speech and proposes a system for converting whispered vowels into normal ones. The system is developed using multilayer perceptron networks and two types of generative adversarial networks. Three metrics are analyzed to evaluate the performance of the system: mel-cepstral distortion, root mean square error of the fundamental frequency, and accuracy with f1-score of a vowel classifier. Overall, the perceptron networks demonstrated better results, with no significant differences observed between male and female voices or the presence/absence of speech silence, except for improved accuracy in estimating the fundamental frequency during the conversion process. © 2025, Universidade do Porto - Faculdade de Engenharia. All rights reserved.

2025

Joint Mobile Iab Node Positioning and Scheduler Selection in Locations with Significant Obstacles

Autores
Correia, PF; Coelho, A; Ricardo, M;

Publicação
Joint European Conference on Networks and Communications & 6G Summit, EuCNC/6G Summit 2025, Poznan, Poland, June 3-6, 2025

Abstract

2025

A Vision-aided Open Radio Access Network for Obstacle-aware Wireless Connectivity

Autores
Simões, C; Coelho, A; Ricardo, M;

Publicação
20th Wireless On-Demand Network Systems and Services Conference, WONS 2025, Hintertux, Austria, January 27-29, 2025

Abstract
High-frequency radio networks, including those operating in the millimeter-wave bands, are sensible to Line-of-Sight (LoS) obstructions. Computer Vision (CV) algorithms can be leveraged to improve network performance by processing and interpreting visual data, enabling obstacle avoidance and ensuring LoS signal propagation. We propose a vision-aided Radio Access Network (RAN) based on the O-RAN architecture and capable of perceiving the surrounding environment. The vision-aided RAN consists of a gNodeB (gNB) equipped with a video camera that employs CV techniques to extract critical environmental information. An xApp is used to collect and process metrics from the RAN and receive data from a Vision Module (VM). This enhances the RAN's ability to perceive its surroundings, leading to better connectivity in challenging environments. © 2025 IFIP.

2025

A Framework to Develop and Validate RL-Based Obstacle-Aware UAV Positioning Algorithms

Autores
Shafafi, K; Ricardo, M; Campos, R;

Publicação
CoRR

Abstract

2025

Autonomous Vision-Aided UAV Positioning for Obstacle-Aware Wireless Connectivity

Autores
Shafafi, K; Ricardo, M; Campos, R;

Publicação
CoRR

Abstract

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