Binaural wind noise cancellation for hearing aids based on head-related transfer function cues

Nakashima, Hideharu; Kouyama, Ryousuke; Hiruma, Nobuhiko; Fujisaka, Yoh-ichi

doi:10.1250/ast.39.40

Cited by 1 publication

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 12 shows the results of the directionality test for (a) target signal and (b) FWF-based method. It indicated that applying the FWF-based method did not lead to any negative effect on the perceived direction, similar to the previously proposed STFT-based method [13], as can be seen from the Figs. 12(a) and 12(b).…”

Section: Directionality Testsupporting

confidence: 80%

“…In this paper, we proposed a low-delay wind noise cancellation algorithm for binaural hearing aids. It was difficult to implement the previously proposed algorithm [13], which required long analysis frame lengths to ensure high resolutions in the low-frequency region, in actual hearing aids from the viewpoint of processing latency for sound transmission from the input to the output. Applying the FWF to the analysis and synthesis stages of our system cleared the way for a trade-off relationship between processing latency and frequency resolution.…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, when hearing aids on both the left and right ears work independently, the perception of the direction of arrival (DOA) and distance to the desired signal position will be uncertain. To preserve spatial information, a binaural wind noise cancellation algorithm using the characteristics of head-related transfer functions (HRTFs) was proposed by the authors [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…In a previous study [13], we demonstrated the advantage of maintaining spatial information in the short-time fast-Fourier-transform-based binaural wind noise cancellation method (STFT-based method), through comparisons with the conventional method, by performing psychoacoustic experiments (externality and directionality tests). However, 512 samples were required for the frequency analysis, to obtain a frequency resolution of 31.25 Hz for a sampling rate of 16 kHz.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Low-delay wind noise cancellation with preservation of spatial information for binaural hearing aids

Hiruma¹,

Nakashima

Fujisaka³

2018

Acoust. Sci. & Tech.

Self Cite

View full text Add to dashboard Cite

Wind noise annoys hearing-aid users, and it is hard to attach a windscreen to a hearing-aid microphone, for cosmetic reasons. Some hearing-aid devices reduce the low-frequency components of input signals by using high-pass filters to suppress the wind noise. Although wind noise can be attenuated by this approach, the perceived binaural information of the desired signals will also be degraded simultaneously, resulting in partial information loss. We had previously proposed a shorttime fast-Fourier-transform-based (STFT-based) binaural wind noise cancellation algorithm that preserves binaural cues. This algorithm required a frame length of 32 ms to maintain a high frequency resolution. However, it is known that the tolerable group delay for mild hearing loss should be less than approximately 5 ms, in the high-frequency region. In this paper, we propose a low-delay binaural wind noise cancellation algorithm that uses a frequency-warping filter. The processing latency of this algorithm is shorter than the tolerable delay. The objective evaluation results-signal-to-noise ratios and perceptual evaluation of speech quality (PESQ) scores-were improved while maintaining a low latency. Subjective experiments demonstrated that the proposed method produced almost the same score as our previous STFT-based method, in terms of the directionality of output signals.

show abstract

Section: Directionality Testsupporting

confidence: 80%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations