In this paper, a single-channel adaptive noise canceller (SCANC) is proposed to enhance heart sounds during auscultation. Heart sounds provide important information about the condition of the heart, but other sounds interfere with heart sounds during auscultation. The adaptive noise canceller (ANC) is widely used to reduce noises from biomedical signals, but it is not suitable for enhancing auscultatory sounds acquired by a stethoscope. While the ANC needs two inputs, a stethoscope provides only one input. Other approaches, such as ECG gating and wavelet de-noising, are rather complex and difficult to implement as real-time systems. The proposed SCANC uses a single-channel input based on Heart Sound Inherency Indicator and reference generator. The architecture is simple, so it can be easily implemented in real-time systems. It was experimentally confirmed that the proposed SCANC is efficient for heart sound enhancement and is robust against the heart rate variations.

In resetting attacks against a proof system, a prover or a verifier is reset and enforced to use the same random tape on various inputs as many times as an adversary may want. Recent deployment of cloud computing gives these attacks a new importance. This paper shows that argument systems for any NP language that are both resettably-sound and resettable zero-knowledge are possible by a constant-round protocol in the BPK model. For that sake, we define and construct a resettably-extractable conditional commitment scheme.

In the channel measurement and characterization, selecting a suitable excitation signal for a specified scenario is the primary task. This letter describes several selecting criteria of the excitation signal for channel sounding. And then the popular types of probing signals are addressed and through simulations their accuracy performances are compared in time-varying channels. The conclusion is the Constant Amplitude Zero Auto-Correlation (CAZAC) sequence yields better results in time-varying scenarios.

Conventional features for Automatic Speech Recognition and Sound Event Recognition such as Mel-Frequency Cepstral Coefficients (MFCCs) have been shown to perform poorly in noisy conditions. We introduce an auditory feature based on the gammatone filterbank, the Selective Gammatone Envelope Feature (SGEF), for Robust Sound Event Recognition where channel selection and the filterbank envelope is used to reduce the effect of noise for specific noise environments. In the experiments with Hidden Markov Model (HMM) recognizers, we shall show that our feature outperforms MFCCs significantly in four different noisy environments at various signal-to-noise ratios.

A workflow net (WF-net for short) is a Petri net which represents a workflow. There are two important subclasses of WF-nets: extended free-choice (EFC for short) and well-structured (WS for short). It is known that most actual workflows can be modeled as EFC WF-nets; Acyclic WS is a subclass of acyclic EFC but has more analysis methods. An acyclic EFC WF-net may be transformed to an acyclic WS WF-net without changing the external behavior of the net. We name such a transformation Acyclic EFC WF-net refactoring. We give a formal definition of acyclic EFC WF-net refactoring problem. We also give a necessary condition and a sufficient condition for solving the problem. Those conditions can be checked in polynomial time. These result in the enhancement of the analysis power of acyclic EFC WF-nets.

This paper describes a method for estimating Direction Of Arrival (DOA) of multiple sound sources in full azimuth with three microphones. Estimating DOA with paired microphone arrays creates imaginary sound sources because of time delay of arrival (TDOA) being identical between real and imaginary sources. Imaginary sound sources can create chronic problems in multiple Sound Source Localization (SSL), because they can be localized as real sound sources. Our proposed approach is based on the observation that each microphone array creates imaginary sound sources, but the DOA of imaginary sources may be different depending on the orientation of the paired microphone array. With the fact that a real source would always be localized in the same direction regardless of the array orientation, we can suppress the imaginary sound sources by minimum filtering based on Steered Response Power – Phase Transform (SRP-PHAT) method. A set of experiments conducted in a real noisy environment showed that the proposed method was accurate in localizing multiple sound sources.

Non-negative matrix factorization (NMF) is widely used for monaural musical sound source separation because of its efficiency and good performance. However, an additional clustering process is required because the musical sound mixture is separated into more signals than the number of musical tracks during NMF separation. In the conventional method, manual clustering or training-based clustering is performed with an additional learning process. Recently, a clustering algorithm based on the mel-frequency cepstrum coefficient (MFCC) was proposed for unsupervised clustering. However, MFCC clustering supplies limited information for clustering. In this paper, we propose various timbre features for unsupervised clustering and a clustering algorithm with these features. Simulation experiments are carried out using various musical sound mixtures. The results indicate that the proposed method improves clustering performance, as compared to conventional MFCC-based clustering.

Many researchers have proposed ultrasound imaging techniques for product inspection; however, most of these techniques are aimed at detecting the existence of flaws in products. The acquisition of an accurate three-dimensional image using ultrasound has the potential to be a useful product inspection tool. In this paper we apply the Envelope algorithm, which was originally proposed for accurate UWB (Ultra Wide-Band) radar imaging systems, to ultrasound imaging. We show that the Envelope algorithm results in image deterioration, because it is difficult for ultrasound measurements to achieve high signal to noise (S/N) ratio values as a result of a high level of noise and interference from the environment. To reduce errors, we propose two adaptive smoothing techniques that effectively stabilize the estimated image produced by the Envelope algorithm. An experimental study verifies that the proposed imaging algorithm has accurate 3-D imaging capability with a mean error of 6.1 µm, where the transmit center frequency is 2.0 MHz and the S/N ratio is 23 dB. These results demonstrate the robustness of the proposed imaging algorithm compared with a conventional Envelope algorithm.

An efficient method is proposed for reconstructing speakerphone-mode cellular phone sound. The overall transfer function from digital PCM signals stored in a cellular phone to dummy head-recorded signals is modeled as a combination of a cellular phone transfer function (CPTF) and a cellular phone-to-listener transfer function (CPLTF). The CPTF represents the linear and nonlinear characteristics of a cellular phone and is modeled by the Volterra model. The CPLTF represents the effect of the path from a cellular phone to a dummy head and is measured. Listening tests show the effectiveness of the proposed method. An application scenario of the proposed method is also addressed for sound quality assessment of cellular phones in speakerphone mode.

The Workflow Management Coalition, WfMC for short, has given a protocol for interorganizational workflows, interworkflows for short. In the protocol, an interworkflow is constructed by connecting two or more existing workflows; and there are three models to connect those workflows: chained, nested, and parallelsynchronized. Business continuity requires the interworkflow to preserve the behavior of the existing workflows. This requirement is called behavioral inheritance, which has three variations: protocol inheritance, projection inheritance, and life-cycle inheritance. Van der Aalst et al. have proposed workflow nets, WF-nets for short, and have shown that the behavioral inheritance problem is decidable but intractable. In this paper, we first show that all WF-nets of the chained model satisfy life-cycle inheritance, and all WF-nets of the nested model satisfy projection inheritance. Next we show that soundness is a necessary condition of projection inheritance for an acyclic extended free choice WF-net of the parallelsynchronized model. Then we prove that the necessary condition can be verified in polynomial time. Finally we show that the necessary condition is a sufficient condition if the WF-net is obtained by connecting state machine WF-nets.

This paper presents the development of a sound–specific vibration interface and its evaluation results by playing three commercial games with the interface. The proposed interface complements the pitfalls of existing frequency–based vibration interfaces such as vibrating headsets, mouses, and joysticks. Those interfaces may bring negative user experiences by generating incessant vibrations because they vibrate in response to certain sound frequencies. But the proposed interface which responds to only target sounds can improve user experiences effectively. The hardware and software parts of the interface are described; the structure and the implementation of a wrist pad that delivers vibration are discussed. Furthermore, we explain a sound-matching algorithm that extracts sound characteristics and a GUI-based pattern editor that helps users to design vibration patterns. The results from evaluating the performance show that the success ratio of the sound matching is over 90% at the volume of 20 dB and the delay time is around 400 msec. In the survey about user experiences, the users evaluates that the interface is more than four times effective in improving the reality of game playing than without using the vibration interfaces, and two times than the frequency–based ones.

The least-squares probabilistic classifier (LSPC) is a computationally-efficient alternative to kernel logistic regression. However, to assure its learned probabilities to be non-negative, LSPC involves a post-processing step of rounding up negative parameters to zero, which can unexpectedly influence classification performance. In order to mitigate this problem, we propose a simple alternative scheme that directly rounds up the classifier's negative outputs, not negative parameters. Through extensive experiments including real-world image classification and audio tagging tasks, we demonstrate that the proposed modification significantly improves classification accuracy, while the computational advantage of the original LSPC remains unchanged.

This paper proposes a system called Neary that detects conversational fields based on similarity of auditory situation among users. The similarity of auditory situation between each pair of the users is measured by the similarity of frequency property of sound captured by head-worn microphones of the individual users. Neary is implemented with a simple algorithm and runs on portable PCs. Experimental result shows Neary can successfully distinguish groups of conversations and track dynamic changes of them. This paper also presents two examples of Neary deployment to detect user contexts during experience sharing in touring at the zoo and attending an academic conference.

In this paper, we propose a method for robot self-position identification by active sound localization. This method can be used for autonomous security robots working in room environments. A system using an AIBO robot equipped with two microphones and a wireless network is constructed and used for position identification experiments. Differences in arrival time to the robot's microphones are used as localization cues. To overcome the ambiguity of front-back confusion, a three-head-position measurement method is proposed. The position of robot can be identified by the intersection of circles restricted using the azimuth differences among different sound beacon pairs. By localizing three or four loudspeakers as sound beacons positioned at known locations, the robot can identify its position with an average error of 7 cm in a 2.53.0 m2 working space in the horizontal plane. We propose adjusting the arrival time differences (ATDs) to reduce the errors caused when the sound beacons are high mounted. A robot navigation experiment was conducted to demonstrate the effectiveness of the proposed position-identification system.

Collecting environmental sound by utilizing high-end mobile phones provides us opportunities to capture rich contextual information in real world. The gathered information can be used for various purposes, ranging from academic research to livelihood support. Furthermore, mobility of mobile phones opens a door for easily forming a dynamic sensing infrastructure, in order to gather fine-grained, but still large-scale data from both spatial and temporal perspectives. However, collecting, analyzing, storing, and sharing of sound data usually involve large energy consumption than scalar data, and like any battery-operated device, mobile phones also face the reality of energy constraints. Because people's first priorities are naturally to use mobile phones for their own purposes, there are occasions when people will not be inclined to allow their mobile phones to be used as sensing devices fearing that they will run out of batteries. Therefore, our research focuses on energy-efficient sensing, to reduce average energy consumption and to extend overall system lifetime. In this paper, we propose a node scheduling scheme for mobile nodes. By applying this scheme, optimized sensing schedules (ACTIVE/SLEEP duty cycles) will be periodically generated at each node. Following the provided schedule during sensing, energy-efficiency can be realized while original Quality of Service (i.e. coverage rate) is retained. Unlike most previous works which were based on ideal binary disk coverage model, our proposal is designed under a probabilistic disk coverage model which takes the characteristic of sound propagation into consideration. Furthermore, this is the first scheme that is adaptable to large-scale mobile sensor networks where topology dynamically changes. An accurate energy consumption model is adopted for evaluating the proposed scheme. Simulation results show that our scheme can reduce up to 48% energy consumption in an ideal environment and up to 31% energy consumption in a realistic environment. The robustness of our scheme is also verified against different type of sensing terrains and communication environments.

In this paper, we propose a new 3D sound rendering method for multiple sound sources with limited computational resources. The method is based on fuzzy clustering, which achieves dual benefits of two general methods based on amplitude-panning and hard clustering. In embedded systems where the number of reproducible sound sources is restricted, the general methods suffer from localization errors and/or serious quality degradation, whereas the proposed method settles the problems by executing clustering-process and amplitude-panning simultaneously. Computational cost evaluation based on DSP implementation and subjective listening test have been performed to demonstrate the applicability for embedded systems and the effectiveness of the proposed method.

The code division multiplexing (CDM)-based MIMO channel sounder architecture is efficient at measuring fast fading MIMO channels. This paper examines loosely synchronous (LS), CAZAC, Kasami, and Chaotic sequences as probing signals in the CDM architecture. After comparing the performance of the channel measurement among the sequences, it is concluded that the LS sequences are the most appropriate codes for the probing signals. However, because LS sequences have a significant drawback in that the number of transmit antennas is limited to less than 4, we propose using a hybrid architecture combining CDM with TDM for supporting a greater number of transmit antennas. The simulation results show that the proposed scheme can improve the measurement performance when more than 4 transmit antennas are used.

In real environments, the presence of ambient noise and room reverberations seriously degrades the accuracy in sound source localization. In addition, conventional sound source localization methods cannot localize multiple sound sources accurately in real noisy environments. This paper proposes a new method of multiple sound source localization using a distributed microphone system that is a recording system with multiple microphones dispersed to a wide area. The proposed method localizes a sound source by finding the position that maximizes the accumulated correlation coefficient between multiple channel pairs. After the estimation of the first sound source, a typical pattern of the accumulated correlation for a single sound source is subtracted from the observed distribution of the accumulated correlation. Subsequently, the second sound source is searched again. To evaluate the effectiveness of the proposed method, experiments of two sound source localization were carried out in an office room. The result shows that sound source localization accuracy is about 99.7%. The proposed method could realize the multiple sound source localization robustly and stably.

We have introduced a new ultrasonic-based localization method that requires only one ultrasonic receiver to locate transmitters. In our previous reports [1],[2], we conducted several fundamental experiments, and proved the feasibility and accuracy of our system. However the performance in a more realistic environment has not yet been evaluated. In this paper, we have extended our localization system into a robot tracking system, and conducted experiments where the system tracked a moving robot. Localization was executed both by our proposed method and by the conventional TOA method. The experiment was repeated with different density of receivers. Thus we were able to compare the accuracy and the scalability between our proposed method and the conventional method. As a result 90-percentile of the position error was from 6.2 cm to 14.6 cm for the proposed method, from 4.0 cm to 6.1 cm for the conventional method. However our proposed method succeeded in calculating the position of the transmitter in 95% out of total attempts of localization with sparse receivers (4 receivers in about 5 m 5 m area), whereas the success rate was only 31% for the conventional method. From the result we concluded that although the proposed method is less accurate it can cover a wider area with sparse receivers than the conventional method. In addition to the dynamic tracking experiments, we also conducted some localization experiments where the robot stood still. This was because we wanted to investigate the reason why the localization accuracy degraded in the dynamic tracking. According to the result, the degradation of accuracy might be due to the systematic error in localization which is dependent on the geometric relationship between the transmitter and the receiver.

In this paper, we propose a new system for controlling radiated sound directivity. The proposed system artificially induces a bending vibration on a planar diaphragm by vibrating it artificially using multiple vibrators. Because the bending vibration in this case is determined by not one but all of the accelerated vibrations, the vibration of the diaphragm can be controlled by modulating the accelerated vibration waveforms relatively for each frequency. As a consequence, the directivity of the radiated sound is also varied. To investigate the feasibility of this system, we constructed a prototype that has for a diaphragm a circular plate-one of the most typical shapes considered for discussing plate vibration-and three vibrators. The measurement data showed visually that with this system, surface vibration and sound directivity change depending on the phases of the accelerated vibrations.