Work on Automatic Music Transcription (AMT) dates back more than 30 years, and has known numerous applications in the fields of music information retrieval, interactive computer systems, and automated musicological analysis (Klapuri, 2004). Due to the difficulty in producing all the information required for a complete musical score, AMT is commonly defined as the computer-assisted process of analyzing an acoustic musical signal so as to write down the musical parameters of the sounds that occur in it, which are basically the pitch, onset time, and duration of each sound to be played. Despite a large enthusiasm for AMT challenges, and several audio-to-MIDI converters available commercially, perfect polyphonic AMT systems are out of reach of today's technology (Klapuri, 2004; Benetos et al., 2013b). To overcome these limitations, a practical engineering solution was to use computational techniques from statistics and digital signal processing, allowing more complex modeling of the musical signal. In this paper, we investigate the use of different Hidden Markov Models (HMMs) in AMT, and evaluate their impacts on transcription performance. HMMs are a ubiquitous tool to model time series data, and have been widely used in various tasks of Music Information Retrieval, especially in music structure analysis by characterizing repetitive patterns (Logan and Chu, 2000) or performing harmonic analysis (Raphael and Stoddard, 2003), chord estimation (Lee and Slaney, 2008) and musicological modeling of note transitions (Ryynanen and Klapuri, 2008). For what concerns the task of AMT, the sequential structure that may be inferred from musical signals can be usefully integrated to systems with HMMs.

With the recent development in mobile computing devices and as the ubiquitous deployment of access points(APs) of Wireless Local Area Networks(WLANs), WLAN based indoor localization systems(WILSs) are of mounting concentration and are becoming more and more prevalent for they do not require additional infrastructure. As to the localization methods in WILSs, for the approaches used to localization in satellite based global position systems are difficult to achieve in indoor environments, fingerprint based localization algorithms(FLAs) are predominant in the RSS based schemes. However, the performance of FLAs has close relationship with the number of APs and the number of reference points(RPs) in WILSs, especially as the redundant deployment of APs and RPs in the system. There are two fatal problems, curse of dimensionality (CoD) and asymmetric matching(AM), caused by increasing number of APs and breaking down APs during online stage. In this paper, a semi-supervised RSS dimensionality reduction algorithm is proposed to solve these two dilemmas at the same time and there are numerous analyses about the theoretical realization of the proposed method. Another significant innovation of this paper is jointing the fingerprint based algorithm with CM-SDE algorithm to improve the localization accuracy of indoor localization.

This paper presents sampling-based speech parameter generation using moment-matching networks for Deep Neural Network (DNN)-based speech synthesis. Although people never produce exactly the same speech even if we try to express the same linguistic and para-linguistic information, typical statistical speech synthesis produces completely the same speech, i.e., there is no inter-utterance variation in synthetic speech. To give synthetic speech natural inter-utterance variation, this paper builds DNN acoustic models that make it possible to randomly sample speech parameters. The DNNs are trained so that they make the moments of generated speech parameters close to those of natural speech parameters. Since the variation of speech parameters is compressed into a low-dimensional simple prior noise vector, our algorithm has lower computation cost than direct sampling of speech parameters. As the first step towards generating synthetic speech that has natural inter-utterance variation, this paper investigates whether or not the proposed sampling-based generation deteriorates synthetic speech quality. In evaluation, we compare speech quality of conventional maximum likelihood-based generation and proposed sampling-based generation. The result demonstrates the proposed generation causes no degradation in speech quality.

In this letter, we propose an algorithm for recovery of sparse and low rank components of matrices using an iterative method with adaptive thresholding. In each iteration, the low rank and sparse components are obtained using a thresholding operator. This algorithm is fast and can be implemented easily. We compare it with one of the most common fast methods in which the rank and sparsity are approximated by $\ell_1$ norm. We also apply it to some real applications where the noise is not so sparse. The simulation results show that it has a suitable performance with low run-time.

Many brands have come to the same conclusion as the fictional Tyrell Corporation in "Blade Runner": by giving their products a past and a personality, they can increase their power of influence on the consumer, writes Wahyd Vannoni. The classic sci-fi film "Blade Runner" is set in 2019 Los Angeles. But one of the 1982 movie's main characters, replicant Leon Kowalski, was created yesterday -- April 10, 2017. Replicants like Kowalski were created by the fictional Tyrell Corporation, who imbued these machines with memories and a sense of personal history to better control them. Now that we've reached Kowalski's "inception day," many brands have come to the same conclusion: by giving their products a past and a personality, they can increase their power of influence on the consumer.

Every now and then, it's wise to stop and recognize the good things in life. And right now, it doesn't get much better than the video game industry. After dozens of Slack conversations about all the exciting titles and hardware coming out this year, a handful of Engadget editors got together to formally celebrate the year in gaming so far. Plus, we gazed into the future and offered suggestions on ways to make 2017 even better. So sit back, clear your mind and join us in an appreciation of everything good the video game industry has to offer in 2017.

Roboticists are getting quite good at making robots with soft, flexible bodies. There are lots of good reasons to do this: Robots with inherent compliance can be safer to work around, more resilient to damage, and can leverage lots of unique methods of locomotion. The issue with soft robots is that you often have to make compromises when it comes to powering them or getting them to move, because those things usually involve the addition of components that aren't soft at all, like batteries and actuators. Over the last week or so, two new methods of soft robot locomotion have shown up in the news: One of them using external magnetic fields, and the other using an electric field to power flapping fins. This robotic ray, which was developed at Zhejiang University in Hangzhou, China, is propelled by soft flapping wings made of dielectric elastomers, which bend when electricity is applied to them.

By establishing analytics as a true business discipline, banks can grasp the enormous potential. Results like these are the good news about analytics. But they are also the bad news. While many such projects generate eye-popping returns on investment, banks find it difficult to scale them up; the financial impact from even several great analytics efforts is often insignificant for the enterprise P&L. Some executives are even concluding that while analytics may be a welcome addition to certain activities, the difficulties in scaling it up mean that, at best, it will be only a sideline to the traditional businesses of financing, investments, and transactions and payments.

The second edition of DES Digital Business World Congress (DES2017), the world's largest international forum on digital transformation, will take place in Madrid (IFEMA) over the 23, 24 and 25 May. International experts in Cyber-security, the Internet of Things (IoT), AI, Cloud, Blockchain, Big data and analytics and leadership, diversity and talent in the new age of digitalisation will be present at the event. Companies including Accenture, Fujitsu, IBM, Wipro, LinkedIn, Mediacloud, Microsoft, EMC, Everis, Google, HP Enterprise, Huawei, Intel, T-Systems, Vmware, Berepublic, Altran, CA Technologies, Dynatrace, Ericsson, FHios, Improove, Konica Minolta, Lenovo, SAS, Schneider Electric, Seidor, Siemens and UST Global have already placed their trust in DES Digital Business World Congress as a meeting point for digital transformation. The world's largest digital transformation congress will once again bring together the knowledge of more than 450 international speakers on subjects such as Digital Leadership, Cloud, IoT, Cyber-security, Big Data and Analytics, as well as up-and-coming technologies such as Blockchain, AI and Robotics, in an international congress with a total of more than 120 hours of conferences. Alex Tapscott, co-author of'Blockchain Revolution: How the technology behind Bitcoin is changing money, business and the world' will set forth the theory of how Blockchain will lead to a new landscape of development in areas as diverse as health, education, government and public administration, finance and business.

Microsoft has pulled the plug on Windows Vista, just over ten years after launching the operating system. It's considered one of the biggest disappointments in the company's history, proving an unpopular successor to the excellent Windows XP. Vista attracted widespread criticism for performance issues and didn't always play nice with customers' peripherals. "Microsoft has provided support for Windows Vista for the past 10 years, but the time has come for us, along with our hardware and software partners, to invest our resources towards more recent technologies so that we can continue to deliver great new experiences," Microsoft said today. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.