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SPS Newsletter Article

Speech enhancement and speech separation are two related tasks, whose purpose is to extract either one or more target speech signals, respectively, from a mixture of sounds generated by several sources.

Self-awareness and self-organization have a long history in biology, psychology, medicine, engineering and (more recently) computing. In the past decade this has inspired new self-aware/self-organizing strategies for building resilient computing platforms that can adapt to the (often conflicting) challenges...

In many emerging applications, it is of paramount interest to learn hidden parameters from data. For example, self-driving cars may use onboard cameras to identify pedestrians, highway lanes, or traffic signs in various light and weather conditions.

Augmented reality devices of the future will likely fuse sensor data from several modalities, allowing multichannel speech enhancement algorithms to exploit, for example, head orientation and accurately estimated source directions.

Voice conversion (VC) is a significant aspect of artificial intelligence. It is the study of how to convert one’s voice to sound like that of another without changing the linguistic content.

Crowdsourcing has emerged as a powerful paradigm for tackling various machine learning, data mining, and data science tasks, by enlisting inexpensive crowds of human workers, or annotators, to accomplish learning and inference tasks.

Thanks to their ability to monitor physical activity and health-related parameters, wearable devices are becoming nowadays more and more popular. In addition to what they already offer, an interesting capability achievable through such devices is biometric recognition.

Over the past twenty years, functional connectivity of the human brain has been studied using tools from complex network theory. One such tool is community detection which  is  fundamental for uncovering the links between structure and function in complex networks.

The IEEE Signal Processing Society (SPS) is happy to announce that Prof. Yonggang Wen will be the new Editor-in-Chief (EIC) of the IEEE Transactions on Multimedia (T-MM). His three-year term will be from January 2023 to December 2025.

Intelligent reflecting surface (IRS) has recently emerged as a promising paradigm for future wireless communications. Owing to its remarkable capability in reshaping the propagation environment, IRS has a great potential to boost spectral efficiency, mitigate interference, and enhance physical security. 

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