Speech enhancement using bone- and air-conducted signals and adaptive GFLANN filter

Xiao, Ran; Xiao, Yegui; Wei, Hongyun; Hasegawa, Koji

doi:10.1109/wcsp.2016.7752692

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…The designed linear phase FIR filter improves the quality of bone conducted speech with speech enhancement method, at around filter length 64 can be tolerably utilized without effected by filter length [3]. According to Ran Xaio et al [19], artificial neural network based linear and non-linear adaptive noise cancellers (ANC) is utilized to improve the speech de-no semantic for BCS and ACS signals. At noisy conditions, high frequency components are recovered by the proposed ANC and outperforms its links for FIR filter, Singh et al [24], by regenerating sounds from Mel frequency ceptrum [MFC] coefficients, the mitigated frequency components have no effect, to overcome this effect and to improve of low frequency components of BCS signal, introduced a wavelet transform for the removal of noise from same speech by utilizing anti phase high frequency components in speech.…”

Section: Brief Review On Approachesmentioning

confidence: 99%

A Study to Analyze Enhancement Techniques on Sound Quality for Bone Conduction and Air Conduction Speech Processing

Subbaiah

Deepthi

2020

SCPE

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In recent years, enhancing speech signal for communications become more complex due to the environmental noises for military and navel applications. Many researchers analyzed and developed complex algorithms and expressed ways to enhance speech signal for both Bone Conducted Speech (BCS) and Air Conducted Speech (ACS) processing techniques. BCS signal is vigorous for outer environmental noises and with low quality signal. ACS signal is sensitive for environmental noises nut rigid in amplitude and high frequencies.Here we have reviewed and investigated various articles to explore their ideas in speech processing for enhancing intelligibility of sound quality.

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Section: Brief Review On Approachesmentioning

confidence: 99%

A Study to Analyze Enhancement Techniques on Sound Quality for Bone Conduction and Air Conduction Speech Processing

Subbaiah

Deepthi

2020

SCPE

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“…For example, in [3], BCM speech is utilized to estimate the speech present probability, and in [4], it is used to help trace the pitch. Other representative works include [5]- [9]. AM speech is indispensable in this kind of algorithms, but it is meaningful to enhance BCM speech directly, because AM speech can be completely unintelligible and become useless in some occasions.…”

Section: Introductionmentioning

confidence: 99%

Spectra Restoration of Bone-Conducted Speech via Attention-Based Contextual Information and Spectro-Temporal Structure Constraint

Zheng

Cao

Yang

et al. 2019

IEICE Trans. Fundamentals

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Compared with acoustic microphone (AM) speech, boneconducted microphone (BCM) speech is much immune to background noise, but suffers from severe loss of information due to the characteristics of the human-body transmission channel. In this letter, a new method for the speaker-dependent BCM speech enhancement is proposed, in which we focus our attention on the spectra restoration of the distorted speech. In order to better infer the missing components, an attention-based bidirectional Long Short-Term Memory (AB-BLSTM) is designed to optimize the use of contextual information to model the relationship between the spectra of BCM speech and its corresponding clean AM speech. Meanwhile, a structural error metric, Structural SIMilarity (SSIM) metric, originated from image processing is proposed to be the loss function, which provides the constraint of the spectro-temporal structures in recovering of the spectra. Experiments demonstrate that compared with approaches based on conventional DNN and mean square error (MSE), the proposed method can better recover the missing phonemes and obtain spectra with spectro-temporal structure more similar to the target one, which leads to great improvement on objective metrics.

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A DNN Based Adaptive Filter for Speech Enhancement

Pradeep Kumar,

Sheela

2024

2024 Second International Conference on Data Science and Information System (ICDSIS)

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Speech enhancement using bone- and air-conducted signals and adaptive GFLANN filter

Cited by 4 publications

References 9 publications

A Study to Analyze Enhancement Techniques on Sound Quality for Bone Conduction and Air Conduction Speech Processing

A Study to Analyze Enhancement Techniques on Sound Quality for Bone Conduction and Air Conduction Speech Processing

Spectra Restoration of Bone-Conducted Speech via Attention-Based Contextual Information and Spectro-Temporal Structure Constraint

A DNN Based Adaptive Filter for Speech Enhancement

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