Noise suppression method by jointly using bone- and air-conducted speech signals

Ikuta, Akira; Orimoto, Hisako; Gallagher, Gerard

doi:10.3397/1/376640

Cited by 4 publications

(4 citation statements)

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“…On the other hand, in the case of higher noises, the proposed method obtains better results than the compared method. Furthermore, in comparison with our previous method [7] with complicated algorithm, almost the same accurate estimation results are obtained as the proposed method. Therefore, the superiority of the proposed method adopting the simplified algorithm could be confirmed.…”

Section: Methodssupporting

confidence: 62%

“…Therefore, many improvements are necessary for the noise cancellation method to apply it to actual speech signal processing. From the above viewpoint, in our preciously reported study, a noise cancellation method was proposed by using air-and bone-conducted speech signals in the situation contaminated by non-Gaussian and non-white noises [7].…”

Section: Introductionmentioning

confidence: 99%

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Noise Cancellation Algorithm Based on Air- and Bone-Conducted Speech Signals by Considering an Unscented Transformation Method

Orimoto¹,

Ikuta²

2019

Adv. sci. technol. eng. syst. j.

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Air-and Bone-conducted UT Method Noise control is essential when applying speech recognition in noisy environments such as factories. In this study, a signal processing for noise cancellation is proposed by using a noise-insensitive bone-conducted speech signal together with an air-conducted speech signal. The speech signal is generally expressed by a nonlinear model. The extended Kalman filter is very famous as a state estimation method for nonlinear systems. However, this filter needs a linearized approximation model for the nonlinear systems. By using the sample point called Sigma point, the unscented Kalman filter (UKF) can be applied to the nonlinear system model without linear approximation. In this study, new type method is proposed based on the UKF. Although UKF considers Gaussian noise, an extended UKF considering non-Gaussian noise is proposed. A noise cancellation method is derived by use of air-and bone-conducted speech signals. The validity of this method is investigated by using both conducted speech signals measured in a noisy real environment.

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Section: Methodssupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Noise Cancellation Algorithm Based on Air- and Bone-Conducted Speech Signals by Considering an Unscented Transformation Method

Orimoto¹,

Ikuta²

2019

Adv. sci. technol. eng. syst. j.

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“…Furthermore, the estimated results by the previously reported method [10] are shown in Figure 12 for the male speech signal and in Figure 13 for the female speech signal.…”

Section: Application To Real Speech Signalmentioning

confidence: 98%

“…From the above viewpoint, in our previously reported study, a noise suppression algorithm for the actual speech signals without requirement of the assumption of Gaussian white noise has been proposed [9]. Furthermore, in our previous study, a signal processing method to remove the noise for actual speech signals was proposed by jointly using the measured data of bone-and air-conducted speeches [10]. However, the algorithm of the previous method was highly complicated because it utilized lower and higher order correlations between the original speech signals, bone-and air-conducted speeches.…”

Section: Introductionmentioning

confidence: 99%

Speech Signal Detection Based on Bayesian Estimation by Observing Air-Conducted Speech under Existence of Surrounding Noise with the Aid of Bone-Conducted Speech

Orimoto¹,

Ikuta²,

Hasegawa³

2021

IIM

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In order to apply speech recognition systems to actual circumstances such as inspection and maintenance operations in industrial factories to recording and reporting routines at construction sites, etc. where hand-writing is difficult, some countermeasure methods for surrounding noise are indispensable. In this study, a signal detection method to remove the noise for actual speech signals is proposed by using Bayesian estimation with the aid of bone-conducted speech. More specifically, by introducing Bayes' theorem based on the observation of air-conducted speech contaminated by surrounding background noise, a new type of algorithm for noise removal is theoretically derived. In the proposed speech detection method, bone-conducted speech is utilized in order to obtain precise estimation for speech signals. The effectiveness of the proposed method is experimentally confirmed by applying it to air-and bone-conducted speeches measured in real environment under the existence of surrounding background noise.

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Speech Extraction Method with Help of Bone-Conducted Sound under Existence of Background Noise

Orimoto,

Ikuta

2023

IEEJ Trans.EIS

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Noise suppression method by jointly using bone- and air-conducted speech signals

Cited by 4 publications

References 0 publications

Noise Cancellation Algorithm Based on Air- and Bone-Conducted Speech Signals by Considering an Unscented Transformation Method

Noise Cancellation Algorithm Based on Air- and Bone-Conducted Speech Signals by Considering an Unscented Transformation Method

Speech Signal Detection Based on Bayesian Estimation by Observing Air-Conducted Speech under Existence of Surrounding Noise with the Aid of Bone-Conducted Speech

Speech Extraction Method with Help of Bone-Conducted Sound under Existence of Background Noise

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