DIT-Artículos
URI permanente para esta colecciónhttps://hdl.handle.net/10953/226
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Examinando DIT-Artículos por Autor "Cabañas-Molero, Pablo Antonio"
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Ítem Multimodal speaker diarization for meetings using volume-evaluated SRP-PHAT and video analysis(Springer, 2018-04-11) Cabañas-Molero, Pablo Antonio; Lucena, Manuel; Fuertes, José Manuel; Vera-Candeas, Pedro; Ruiz-Reyes, NicolásSpeaker diarization is traditionally defined as the problem of determining “who speaks when” given an audio or video stream. This is an important task in many applications for meeting rooms, including automatic transcription of conversations, camera steering or content summarization. When the room is equipped with microphone arrays and cameras, speakers can be distinguished according to their location and the problem can be addressed through localization techniques. This article proposes a multimodal speaker diarization system for meeting environments based on a modified SRP-PHAT function evaluated on space volumes rather than discrete points. In our system, this function is used in combination with a circular array, enabling audio-based localization based on the selection of local maxima. Voicing detection is used to detect speech frames, whereas video analysis is introduced to aid in the decision when users move or simultaneously speak. The approach is evaluated on the well-known AMI dataset with approximately 100 hours of realistic meeting recordings and shows an average diarization error rate of 21% – 25%.Ítem The music demixing machine: toward real-time remixing of classical music(Springer, 2023-04-06) Cabañas-Molero, Pablo Antonio; Muñoz-Montoro, Antonio Jesús; Vera-Candeas, Pedro; Ranilla, JoséClassical music, unlike popular music, is usually recorded live with close microphone techniques. For this reason, isolated tracks are not available to create the final mixture/stream, and so the mixing process requires greater effort. Source separation methods are a potential solution to this problem. However, current algorithms are not fast enough to yield real-time separation in professional setups with dozens of microphones and sources. In this paper, we propose a fast approach consisting of a panning-based multichannel non-negative matrix factorization model to separate classical music. We tested the system on real professional recordings, where we were able to reach real-time with very low latency and promising quality.