Masanori Kato

Bio: Masanori Kato is an academic researcher from NEC. The author has contributed to research in topics: Noise & Noise floor. The author has an hindex of 9, co-authored 42 publications receiving 418 citations.

Noise suppression with high speech quality based on weighted noise estimation and MMSE STSA

Abstract: This paper proposes a high speech quality noise suppression method based on weighted noise estimation and MMSE STSA. The proposed method continuously updates the noise estimate, using weighted noisy speech according to the estimated speech-to-noise ratio. In order to fully utilize the improvement offered by noise estimation, the spectral gain is corrected according to the estimated speech-to-noise ratio. By using accurate noise estimation, more accurate SNR than in the conventional method is obtained, which helps to reduce distortion in the enhanced speech. In subjective speech quality evaluations, the five-stage MOS was improved by 0.35 and 0.40 at the maximum, respectively, for the cases in which the speech was encoded and was not encoded after noise suppression. The improved version, which was developed on the basis of the proposed noise suppressor, satisfies all 3GPP minimum requirements for speech quality and has been installed in a commercially available model. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(2): 43–53, 2006; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/ecjc.20145

Noise Suppression with High Speech Quality Based on Weighted Noise Estimation and MMSE STSA

Abstract: A noise suppression algorithm with high speech quality based on weighted noise estimation and MMSE STSA is proposed. The proposed algorithm continuously updates the noise estimate by noisy speech weighted in accordance with an estimated SNR. The spectral gain is modified with the estimated SNR so that it can better utilize the improvement in noise estimation. Subjective evaluation results show that five-grade mean opinion scores of the new algorithm are improved by as much as 0.93 and 0.35, compared with the original MMSE STSA and the EVRC noise suppression algorithm, respectively.

Noise removing method and device

Abstract: A noise removing device comprising a conversion unit for converting an input signal into a frequency region, an SNR calculation unit for using a frequency region signal to determine a signal-to-noise ratio (SNR), a suppression factor generating unit for determining a suppression factor based on the SNR, a suppression factor correction unit for correcting a suppression factor to determine a corrected suppression factor, a multiplying unit for using a corrected suppression factor to weighting a frequency region signal, and an inversion unit for converting a weighted frequency region signal into a time region signal, the noise removing device being preferably used to determine an SNR by calculating a weighted deteriorated voice power spectrum from the power spectrum of a deteriorated voice and that of an estimated noise.

Method and apparatus for removing noise

Abstract: PROBLEM TO BE SOLVED: To provide a method and an apparatus for removing noise capable of obtaining an emphasized voice with reduced distortion and noise regardless of types of noise and values of an SNR SOLUTION: The apparatus has a weighted degraded-voice calculating section 14 for calculating a weighted degraded-voice power spectrum from a degraded voice power spectrum and an estimated noise power spectrum Also, the apparatus has a suppression coefficient correcting section for calculating a corrected suppression coefficient in response to the value of the SNR and a suppression coefficient COPYRIGHT: (C)2002,JPO

Noise suppressing method and apparatus and computer program

Abstract: A noise suppressing method and an apparatus wherein a high quality of noise suppression can be achieved by use of a reduced amount of calculation. Input signals are converted to frequency domain signals, the bands of which are integrated to obtain integrated frequency domain signals. These integrated frequency domain signals are used to determine an estimated noise. This estimated noise and the integrated frequency domain signals are used to determine a suppression factor, which is then used to weight the frequency domain signals, thereby suppressing the noise included in the input signals.

MMSE based noise PSD tracking with low complexity

Abstract: Most speech enhancement algorithms heavily depend on the noise power spectral density (PSD). Because this quantity is unknown in practice, estimation from the noisy data is necessary. We present a low complexity method for noise PSD estimation. The algorithm is based on a minimum mean-squared error estimator of the noise magnitude-squared DFT coefficients. Compared to minimum statistics based noise tracking, segmental SNR and PESQ are improved for non-stationary noise sources with 1 dB and 0.25 MOS points, respectively. Compared to recently published algorithms, similar good noise tracking performance is obtained, but at a computational complexity that is in the order of a factor 40 lower.

System and method for adaptive intelligent noise suppression

Abstract: Systems and methods for adaptive intelligent noise suppression are provided. In exemplary embodiments, a primary acoustic signal is received. A speech distortion estimate is then determined based on the primary acoustic signal. The speech distortion estimate is used to derive control signals which adjust an enhancement filter. The enhancement filter is used to generate a plurality of gain masks, which may be applied to the primary acoustic signal to generate a noise suppressed signal.

Method and device for speech enhancement in the presence of background noise

Abstract: In one aspect thereof the invention provides a method for noise suppression of a speech signal that includes, for a speech signal having a frequency domain representation dividable into a plurality of frequency bins, determining a value of a scaling gain for at least some of said frequency bins and calculating smoothed scaling gain values. Calculating smoothed scaling gain values includes, for the at least some of the frequency bins, combining a currently determined value of the scaling gain and a previously determined value of the smoothed scaling gain. In another aspect a method partitions the plurality of frequency bins into a first set of contiguous frequency bins and a second set of contiguous frequency bins having a boundary frequency there between, where the boundary frequency differentiates between noise suppression techniques, and changes a value of the boundary frequency as a function of the spectral content of the speech signal.

Device and method for analyzing an information signal

Abstract: In order to analyze an information signal, which has a series of blocks of information units, whereby a number of successive blocks of the series of blocks depicts an information entity, identification results for successive fingerprints are prepared (12) while using a series of fingerprints for the series of blocks, whereby an identification result depicts an association of a block of information units with a predetermined information entity. After this, at least two hypotheses are formed (14) from the identification results for the successive fingerprints. A first hypothesis is an assumption for the association of the series of blocks with a first information entity, and the second hypothesis is an assumption for the association of the series of blocks with the second information entity. Afterwards, different hypotheses are tested (16) in order to obtain a test result on the basis of which an assertion concerning the information signal is made (20). This results in obtaining a meaningful and reliable continuous-time analysis of an information signal.

Wind noise reduction

Abstract: By monitoring the wind noise in a location in which a cellular telephone is operating and by applying noise reduction and/or cancellation protocols at the appropriate time via analog and/or digital signal processing, it is possible to significantly reduce wind noise entering into a communication system.