We propose a new blind spatial subtraction array (BSSA) consisting of noise estimator based on independent component analysis (ICA) for efficient speech enhancement. In this paper, first, we theoretically and experimentally point out that ICA is proficient in estimation under non-point-source condition rather than estimation. Therefore, BSSA utilizes as estimator. BSSA, extraction achieved by subtracting the power spectrum signals estimated using from partly enhanced target signal with...

In this paper, we provide a theoretical analysis of the amount musical noise in iterative spectral subtraction, and its optimization method for least generation. To achieve high-quality reduction with low noise, i.e., iteratively applied weak nonlinear signal processing, has been proposed. Although effectiveness reported experimentally, there have no studies. Therefore, formulate generation process by tracing change kurtosis spectra, conduct comparison different parameter settings but same...

In this paper, statistical-model generalizations of independent low-rank matrix analysis (ILRMA) are proposed for achieving high-quality blind source separation (BSS). BSS is a crucial problem in realizing many audio applications, where the sources must be separated using only observed mixture signal. Many algorithms solving have been proposed, especially history component and nonnegative factorization. particular, ILRMA can achieve highest performance music or speech mixtures, assumes both...

In this paper, we provide a new theoretical analysis of the amount musical noise generated via generalized spectral subtraction based on higher order statistics. Power is most commonly used method, and in our previous study assessment theory limited to power domain was proposed. propose generalization for arbitrary exponent parameters. We can thus compare between any domains from results analysis. also clarify that less when choose lower domain; implies there no justification using...

In this paper, to address problems in multichannel music signal separation, we propose a new hybrid method that combines directional clustering and advanced nonnegative matrix factorization (NMF). The aims of separation technology is extract specific target from observed signals contain multiple instrumental sounds. previous studies, various methods using NMF have been proposed, but many remain including poor accuracy lack robustness. To solve these problems, supervised (SNMF) with...

Independent low-rank matrix analysis (ILRMA) is a fast and stable method of blind audio source separation. Conventional ILRMAs assume time-variant (super-)Gaussian models, which can only represent signals that follow super-Gaussian distribution. In this article, we focus on ILRMA based generalized Gaussian distribution (GGD-ILRMA) propose new type GGD-ILRMA adopts sub-Gaussian for the model. We update scheme called iterative projection homogeneous models (GIP-HSM) obtain...

In this paper, we investigate amplitude-based speech enhancement for asynchronous distributed recording. an ad-hoc microphone array context, it is supposed that different devices record speech. As a result, the phase information unreliable due to sampling frequency mismatch. For based on amplitude instead of information, supervised nonnegative matrix factorization (NMF) introduced in time-channel domain. The basis vectors, which represents gain transfer function from source each microphone,...

Audio source separation is an important problem for many audio applications. Independent low-rank matrix analysis (ILRMA) a recently proposed algorithm that employs the statistical independence between sources and low-rankness of time-frequency structure in each source. As reported this paper, we have developed new framework enables us to introduce spatial regularization demixing ILRMA. Since conventional optimization cannot be applied regularized ILRMA, derive novel approach based on...

In this paper, we reveal new findings about the generated musical noise in minimum mean-square error short-time spectral amplitude (MMSE STSA) processing. Recently have proposed a objective metric of based on kurtosis change ratio subtraction (SS). Also found an interesting relationship among degree noise, shapes signal-s probability density function, strength parameter SS This paper is aimed to automatically evaluate sound quality various types reduction methods using ratio. We give...

In this letter, we address monaural source separation based on supervised nonnegative matrix factorization (SNMF) and propose a new penalized SNMF. Conventional SNMF often degrades the performance owing to basis-sharing problem. Our forces nontarget bases become different from target bases, which increases separated sound quality.

We construct a quantum circuit for Shor's factoring algorithm that uses 2n+2 qubits, where n is the length of number to be factored. The depth and size are O(n^3) O(n^3\log n), respectively. qubits used in less than any other ever constructed algorithm. Moreover, about half Beauregard's algorithm, which 2n+3 qubits.

We conduct an objective analysis on musical noise generated by two methods of integrating microphone array signal processing and spectral subtraction. To obtain better reduction, nonlinear have been researched. However, often generates noise. Since such causes discomfort to users, it is desirable that mitigated. Moreover, has recently reported higher-order statistics are strongly related the amount generated. This implies possible optimize integration method from viewpoint not only reduction...

In this paper, we propose a musical-noise-controllable algorithm for array signal processing with the aim high-performance and high-quality noise reduction. Recently, many methods of integrating linear microphone nonlinear reduction have been studied, but these often suffer from problem musical noise. proposed algorithm, channelwise spectral subtraction is applied before adaptive processing. We also introduce new automatic control to obtain strength parameter used in subtraction, which...

Efficient drug discovery relies on accessing diverse small molecules expediently and reliably. Improvements to reliability through machine learning predictions are hampered by poor availability of high-quality reaction data. Here, we introduce an on-demand synthesis platform based a three-component that delivers drug-like overnight. Miniaturization automation enable the execution analysis 50,000 reactions 3 microliter scale with distinct substrates, producing largest public outcome dataset....

In this paper, we address a music signal separation problem, and propose new supervised algorithm for real instrumental employing deformable capability spectral supervision trained in advance. Nonnegative matrix factorization (NMF) is one of the techniques used an audio mixture that consists multiple sources. Conventional NMF has critical problem mismatch between bases advance target sound reduces accuracy separation. To solve advanced employs penalty terms making fit into sound. The results...

This paper addresses an audio source separation problem and proposes a new basis training method for semi-supervised nonnegative matrix factorization (NMF). In conventional NMF, pretrained spectral bases target can represent other undesired interfering sources, which degrade the performance. To solve this problem, we propose of two types supervised bases, discriminative reconstructive, source. stage, are trained to have unique components maximize discrimination ability from whereas...

In this paper, we proposed a new blind speech extraction method consisting of Wiener filtering and noise estimation based on independent component analysis (ICA). First, provide both theoretically experimental investigations proficiency ICA in under non-point-source condition. Next, computer simulation experiment an actual railway-station environment are conducted, their results also indicate that is proficient Finally, newly propose ICA-based estimation, the effectiveness via recognition...

In this paper, we conduct an analysis for reduction of musical noise in integration method microphone array signal processing and nonlinear processing. these days, better reduction, methods have been researched. However, non-linear causes noise. Since such make users uncomfortable, it is desired that mitigated. Moreover, reported higher-order statistics strongly related with the amount generated Thus, analyze integrated processing, based on statistics. Also, propose architecture reducing...

In this paper, we address a stereo signal separation problem and propose new method utilizing both directional clustering superresolution-based supervised nonnegative matrix factorization (NMF) via spectrogram extrapolation using bases. previous studies, hybrid concatenating NMF after was proposed as for multichannel separation. However, has that the extracted suffers from considerable spectral distortion because yields chasms. To solve problem, algorithm regards chasms unseen observations...

A power-assisting device is presented to help elderly patients and with disabilities transfer themselves from beds wheelchairs. The intended contribute a more independent life for the greater utilization of their disabilities. development device, which consists an upper part capable motion in horizontal plane lower vertical plane, discussed. production method power assistance guidance this proposed. Finally, testing performance developed system basic experiment described.

In this paper, we construct a hands-free robot spoken dialogue system based on the real-time blind spatial subtraction array (BSSA) and evaluate system. BSSA is source extraction method, in carried out by subtracting power spectrum of estimated noise signal independent component analysis from target speech partly enhanced signal. Although can reduce efficiently, ICA consumes huge amount computational costs. Thus it difficult to run real-time. newly propose architecture BSSA. with BSSA, 6%...