Long-Term Average Spectrum Characteristics of Portuguese Fado-Canção from Coimbra.

Descriptions of acoustical characteristics of Fado, a Portuguese urban style sung in Lisbon and Oporto, are scarce, particularly concerning Fado-Canção, a related style sung in Coimbra. The present study aims at describing long-term average spectrum (LTAS) parameters of 16 professional singers while singing and reading the lyrics of a typical Fado-Canção. LTAS parameters were investigated in terms of: (1) equivalent sound level (Leq); (2) spectral differences between 3 frequency bands 0-2, 2-5, and 5-8 kHz; and (3) quantification of spectral prominence between 2 and 4 kHz, calculated as the level difference between the peak in this frequency region and a reference trendline between 1 and 5 kHz, henceforth Formant Cluster Prominence (FCP). Given that Fado-Canção, besides Fado and traditional styles, originated also from classical singing, and that previous studies on Fado suggest the absence of a singer's formant cluster, the averaged LTAS for all Fado-Canção singers was further compared to the LTAS of two world-touring opera baritones singing an operatic aria and a lied. Results show that Fado-Canção is commonly sung with a Leq of 86.4 dB and a FCP of about 10 dB, values significantly higher when compared to reading. The FCP in Fado-Canção, although smaller than for the two classical opera singers' examples (14.8 and 20 dB, respectively), suggests that the style preserved some of its original lyrical influence. However, because younger singers present higher energy in the 5-8 kHz region relative to the remaining frequency bands as compared to older singers, it seems that Fado-Canção may be drifting towards non-classical vocal practices. FCP seems to be a promising straightforward method to quantify the degree of formant clustering around the region of the singer's formant in LTAS, allowing comparisons between different singers and singing styles.

Video segmentation based on motion coherence of particles in a video sequence.

This work describes an approach for object-oriented video segmentation based on motion coherence. Using a tracking process based on adaptively sampled points (namely, particles), 2-D motion patterns are identified with an ensemble clustering approach. Particles are clustered to obtain a pixel-wise segmentation in space and time domains. The segmentation result is mapped to an image spatio-temporal feature space. Thus, the different constituent parts of the scene that move coherently along the video sequence are mapped to volumes in this spatio-temporal space. These volumes make the redundancy in the temporal sense more explicit, leading to potential gains in video coding applications. The proposed solution is robust and more generic than similar approaches for 2-D video segmentation found in the literature. In order to illustrate the potential advantages of using the proposed motion segmentation approach in video coding applications, the PSNR of the temporal predictions and the entropies of prediction errors obtained in our experiments are presented, and compared with other methods. Our experiments with real and synthetic sequences suggest that our method also could be used in other image processing and computer vision tasks, besides video coding, such as video information retrieval and video understanding.