Percorrer por autor "Teixeira, Felipe"
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- Acoustic analysis of chronic laryngitis - statistical analysis of sustained speech parametersPublication . Teixeira, João Paulo; Fernandes, Joana Filipa Teixeira; Teixeira, Felipe; Fernandes, Paula OdeteThis paper describes the statistical analysis of a set of features extracted from the speech of sustained vowels of patients with chronic laryngitis and control subjects. The idea is to identify which features can be useful in a classification intelligent system to discriminate between pathologic and healthy voices. The set of features analysed consist in the Jitter, Shimmer Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR) and Autocorrelation extracted from the sound of a sustained vowels /a/, /i/ and /u/ in a low, neutral and high tones. The results showed that besides the absolute Jitter, no statistical significance exist between male and female voices, considering the classification between pathologic or healthy. Any of the analysed parameters is likely to be a statistical difference between control and Chronic Laryngitis groups. This is an important information that these features can be used in an intelligent system to classify healthy from Chronic Laryngitis voices.
- Analysis of the middle and long latency ERP components in SchizophreniaPublication . Costa, Miguel Rocha; Teixeira, Felipe; Teixeira, João PauloSchizophrenia is a complex and disabling mental disorder estimated to affect 21million people worldwide. Electroencephalography (EEG) has proven to be an excellent tool to improve and aid the current diagnosis of mental disorders such as schizophrenia. The illness is comprised of various disabilities associated with sensory processing and perception. In this work, the first 10−200 ms of brain activity after the self-generation via button presses (condition 1) and passive presentation (condition 2) of auditory stimuli was addressed. A time-domain analysis of the event-related potentials (ERPs), specifically the MLAEP, N1, and P2 components, was conducted on 49 schizophrenic patients (SZ) and 32 healthy controls (HC), provided by a public dataset. The amplitudes, latencies, and scalp distribution of the peaks were used to compare groups. Suppression, measured as the difference between both conditions’ neural activity, was also evaluated. With the exception of the N1 peak during condition (1), patients exhibited significantly reduced amplitudes in all waveforms analyzed in both conditions. The SZ group also demonstrated a peak delay in theMLAEP during condition (2) and amodestly earlier P2 peak during condition (1). Furthermore, patients exhibited less andmore N1 and P2 suppression, respectively. Finally, the spatial distribution of activity in the scalp during the MLAEP peak in both conditions, N1 peak in condition (1) and N1 suppression differed considerably between groups. These findings and measurements will be used with the finality of developing an intelligent system capable of accurately diagnosing schizophrenia.
- Characterising industrial tourism in the cross-border region: Portugal and SpainPublication . Scalabrini, Elaine C.B.; Alves, Francisco; Neto, Reginaldo; Teixeira, Felipe; García, Joaquín; Velasco, Miguel; Teixeira, João Paulo; Vaz, Roberto; Fernandes, Paula OdetePurpose | Industrial tourism is an emerging sector highlighting the historical industrial landscape, fostering regional development, community revitalisation, and heritage preservation. Factories, mines, and transport infrastructure can be transformed into museums and interactive spaces. Industrial tourism can also include tours of active industrial sites where production remains the primary focus (Friel et al., 2024; Yan et al., 2024). In this context, this study aims to characterise the industrial heritage of the cross-border region, namely in Terras de Trás-os-Montes (Portugal) and Castilla y León (Spain), in the Douro River region, aiming to showcase opportunities for cross-border tourism development. Methodology/Approach | Firstly, a database was drawn up with the industrial heritage of the two regions under analysis. To do this, a form was drawn up based on previous documents and validated by the team of a project related to industrial tourism. From October 2024 to March 2025, the form was sent to 22 municipalities in Portugal and 80 municipalities in Spain. Ultimately, 1079 industrial heritage sites were registered and statistically analysed to determine their characterisation. Expected Results | Of the 1079 industrial heritage sites, 247 are in Portugal, and 832 are in Spain. The heritage elements were categorised and most related to transport infrastructure (31%), wineries (23.6%), food industries (20.5%), and hydraulic heritage (9.3%). These characteristics align with the attractions offered in the two regions surrounding the River Douro. Portugal presents more transport (34.6%) and wineries (22.7%), and Spain to wineries (26.7%) and food industries (25.1%). It is also clear that most (47.3%) of the heritage sites identified are prepared to receive visitors. This study shows that the categorisation of heritage reflects the richness and historical diversity of the region. Among the main types of heritage identified are wineries, illustrating the strong wine-growing tradition of the Douro River, and transport infrastructure, namely old railway stations and bridges, which highlight witness to the impact of industrialisation on regional connectivity. There are also hydraulic structures, such as water mills and historic dams, which show how water resources have been used for industrial activity over the centuries.
- Classification of control/pathologic subjects with support vector machinesPublication . Teixeira, Felipe; Fernandes, Joana Filipa Teixeira; Guedes, Victor; Candido Junior, Arnaldo; Teixeira, João PauloThe diagnosis of pathologies using vocal acoustic analysis has the advantage of been noninvasive and inexpensive technique compared to traditional technique in use. In this work the SVM were experimentally tested to diagnose dysphonia, chronic laryngitis or vocal cords paralysis. Three groups of parameters were experimented. Jitter, shimmer and HNR, MFCCs extracted from a sustained vowels and MFCC extracted from a short sentence. The first group showed their importance in this type of diagnose and the second group showed low discriminative power. The SVM functions and methods were also experimented using the dataset with and without gender separation. The best accuracy was 71% using the jitter, shimmer and HNR parameters without gender separation.
- Comparative Analysis of Windows for Speech Emotion Recognition Using CNNPublication . Teixeira, Felipe; Soares, Salviano Pinto; Abreu, J.L. Pio; Oliveira, Paulo M.; Teixeira, João PauloThe paper presents the comparison of accuracy in the Speech Emotion Recognition task using the Hamming and Hanning windows for framing the speech and determining the spectrogram to be used as input of a convolutional neural network. The detection of between 4 and 10 emotional states was tested for both windows. The results show significant differences in accuracy between the two window types and provide valuable insights for the development of more efficient emotional state detection systems. The best accuracy between 4 and 10 emotions was 64.1% (4 emotions), 57.8% (5 emotions), 59.8% (6 emotions), 48.4% (7 emotions), 47.8% (8 emotions), 51.4% (9 emotions), and 45.9% (10 emotions). These accuracy is at the state-of-the art level.
- Cured database of sustained speech parameters for chronic laryngitis pathologyPublication . Fernandes, Joana Filipa Teixeira; Teixeira, Felipe; Fernandes, Paula Odete; Teixeira, João PauloThis paper reports the construction and organization of a database of speech parameters extracted from a speech sound database. The database is freely available on internet and the paper intends also theirs advertise for the research community. The database includes the parameters extracted from the sound of sustained vowels produced by a group of Chronic Laryngitis patients and a group of control subjects with similar characteristics concerning gender and age. The set of parameters of this database consists in the Jitter, Shimmer, Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR) and Autocorrelation extracted from the sound of sustained vowels /a/, /i/ and /u/ at low, neutral and high tones.
- Deep-learning in identification of vocal pathologiesPublication . Teixeira, Felipe; Teixeira, João PauloThe work consists in a classification problem of four classes of vocal pathologies using one Deep Neural Network. Three groups of features extracted from speech of subjects with Dysphonia, Vocal Fold Paralysis, Laryngitis Chronica and controls were experimented. The best group of features are related with the source: relative jitter, relative shimmer, and HNR. A Deep Neural Network architecture with two levels were experimented. The first level consists in 7 estimators and second level a decision maker. In second level of the Deep Neural Network an accuracy of 39,5% is reached for a diagnosis among the 4 classes under analysis.
- DROOd: desidratação de fruta e vegetais por ar secoPublication . Fernandes, Joana Filipa Teixeira; Lamas, Ricardo; Pinto, Anaísa; Martins, Rúben; Oliveira, Carlos Manuel Mesquita; Cerdeira, Tânia Filipa Alves; Teixeira, Felipe; Vila Franca, Tiago; Borges, Pedro; Fitas, Tiago; Gouveia, Pedro; Ribeiro, Luís FrölénApresenta-se um equipamento capaz de desidratar alimentos que poderá ser adquirido por pequenos agricultores. A proposta de um equipamento que consegue desidratar os produtos produzidos através de ar seco com uma potência equivalente à de um eletrodoméstico, 1,4 kW, tendo a capacidade de desidratar até 4 kg de frutas ou vegetais. Apresenta-se a simulação do funcionamento do equipamento a secar o equivalente a 23 tomates ou 24 bananas ou 21 laranjas simultaneamente distribuídos em 7 tabuleiros individuais, demorando 10, 8 e 9h, respetivamente, a serem desidratados.
- F0, LPC, and MFCC analysis for emotion recognition based on speechPublication . Teixeira, Felipe; Teixeira, João Paulo; Soares, Salviano; Abreu, J.L. PioIn this work, research was done to understand what is needed to build a database to recognise emotions through speech. Some features that can highlight a good success rate for emotion recognition through speech were investigated. Also studied were some characteristics (symptoms) that can be associated with a specific emotional state. On the other hand, we also studied some features that can be used to identify some emotional states. A System Emotion Recognition (SER) was built with SVM, and the binary analysis was compared with a multi-category analysis. The binary analysis achieved an accuracy of 87.5% and the multi-class 42.6%. The parameters Fundamental Frequency-F0, Linear Predictive Coefficients (LPC), and Mel Frequency Cepstral Coeficients (MFCC) were used. The modest accuracy of this work was achieved using only F0, LPC and MFCC features.
- Harmonic to noise ratio measurement - selection of window and lengthPublication . Fernandes, Joana Filipa Teixeira; Teixeira, Felipe; Guedes, Victor; Candido Junior, Arnaldo; Teixeira, João PauloHarmonic to Noise Ratio (HNR) measures the ratio between periodic and non-periodic components of a speech sound. It has become more and more important in the vocal acoustic analysis to diagnose pathologic voices. The measure of this parameter can be done with Praat software that is commonly accept by the scientific community has an accurate measure. Anyhow, this measure is dependent with the type of window used and its length. In this paper an analysis of the influence of the window and its length was made. The Hanning, Hamming and Blackman windows and the lengths between 6 and 24 glottal periods were experimented. Speech files of control subjects and pathologic subjects were used. The results showed that the Hanning window with the length of 12 glottal periods gives measures of HNR more close to the Praat measures.