Acoustic Equalization for Headphones Using a Fixed Feed-forward Filter

Fabry, Johannes; Konig, Fabio; Liebich, Stefan; Jax, Peter

doi:10.1109/icassp.2019.8682167

Cited by 8 publications

(21 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rather, some components are designed with the improved transmission of the speaking voice in mind, implicitly and automatically “improving” the signal (which, in fact, may introduce unwanted distortions to the transmitted singing voice signal). For instance, some microphones may under certain circumstances add a “bass boost” or a boost to the singers’ formant region between 2 and 4 kHz [10] , and some loudspeakers and earphones may alter the spectral or dynamic composition of the sound via a feature called active noise control (ANC) in an attempt to equalize and attenuate ambient sound [3] .…”

Section: Discussionmentioning

confidence: 99%

“…For instance, some microphones may under certain circumstances add a "bass boost" or a boost to the singers' formant region between 2 and 4 kHz, 16 and some loudspeakers and earphones may alter the spectral or dynamic composition of the sound via a feature called active noise control (ANC) in an attempt to equalize and attenuate ambient sound. 18 This study has been designed as an ad hoc response to the emerging COVID-19 crisis. As such, it may suffer from a number of potential limitations:…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

In-Person or Virtual? – Assessing the Impact of COVID-19 on the Teaching Habits of Voice Pedagogues

2022

View full text Add to dashboard Cite

The social distancing measures implemented world-wide in the wake of the novel Coronavirus (COVID-19) crisis have forced voice pedagogues to alter their teaching habits, likely shifting from customary in-person teaching to virtual teaching. An online survey, distributed world-wide in April/May 2020, investigated how singing voice pedagogues were impacted by the COVID-19 crisis. The collected responses from 387 survey participants suggest that, overall, voice teachers were only moderately satisfied with having to teach virtually, indicating that virtual voice teaching is not a sufficient replacement for in-person teaching. The participants indicated that during virtual teaching the singing voice can be assessed relatively well through features which provide both acoustic and visual clues. In contrast, depending on utilized technology, it may be harder to judge those aspects of the singing voice that are solely defined acoustically, such as dynamic range and spectral composition. This may be explained by limitations imposed by “out of the box” technology for online communication, which is typically optimized for speech instead of singing. This calls for better information on technological solutions for virtual voice teaching.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

In-Person or Virtual? – Assessing the Impact of COVID-19 on the Teaching Habits of Voice Pedagogues

2022

View full text Add to dashboard Cite

show abstract

“…In order to improve the sound quality, sound pressure equalization algorithms can be used that aim at perceptually restoring the open-ear characteristics when a hearing device is used, typically referred to as acoustic transparency. To achieve acoustic transparency, different approaches can be used (Denk et al, 2018a;Fabry et al, 2019;Gupta et al, 2019;Hoffmann et al, 2013;Schepker et al, submitted;Välimäki et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Individualized sound pressure equalization in hearing devices exploiting an electro-acoustic model

Schepker,

Rohden,

Denk

et al. 2021

Preprint

View full text Add to dashboard Cite

To improve sound quality in hearing devices, the hearing device output should be appropriately equalized. To achieve optimal individualized equalization typically requires knowledge of all transfer functions between the source, the hearing device, and the individual eardrum. However, in practice the measurement of all of these transfer functions is not feasible. This study investigates sound pressure equalization using different transfer function estimates. Specifically, an electro-acoustic model is used to predict the sound pressure at the individual eardrum, and average estimates are used to predict the remaining transfer functions. Experimental results show that using these assumptions a practically feasible and close-to-optimal individualized sound pressure equalization can be achieved.

show abstract

“…Since the sound played back by the device is typically delayed compared to the direct sound, so-called combfiltering effects frequently occur which may degrade the perceived sound quality [8,9,10]. Several equalization algorithms for hearing devices have been proposed in the literature [3,4,6,11,12,13,14]. However, often either the direct sound component was neglected in the equalization filter design, e.g., [4], or electro-acoustic components were neglected, e.g., [6].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, it may be desirable to include knowledge about the advanced hearing device processing when designing the equalization filter, e.g., when a hearing loss needs to be compensated. However, including knowledge about advanced hearing device processing has often been neglected in previous research, e.g., [4,6,13,14]. In this paper we propose to include information about both the direct sound component as well as the hearing device processing in the equalization filter design.…”

Section: Introductionmentioning

confidence: 99%

Robust single- and multi-loudspeaker least-squares-based equalization for hearing devices

Schepker¹,

Denk²,

Kollmeier³

et al. 2021

Preprint

View full text Add to dashboard Cite

To improve the sound quality of hearing devices, equalization filters can be used that aim at achieving acoustic transparency, i.e., listening with the device in the ear is perceptually similar to the open ear. The equalization filter needs to ensure that the superposition of the equalized signal played by the device and the signal leaking through the device into the ear canal matches a processed version of the signal reaching the eardrum of the open ear. Depending on the processing delay of the hearing device, comb-filtering artifacts can occur due to this superposition, which may degrade the perceived sound quality. In this paper we propose a unified least-squares-based procedure to design single-and multi-loudspeaker equalization filters for hearing devices aiming at achieving acoustic transparency. To account for non-minimum phase components, we introduce a so-called acausality management. To reduce comb-filtering artifacts, we propose to use a frequency-dependent regularization. Experimental results using measured acoustic transfer functions from a multi-loudspeaker earpiece show that the proposed equalization filter design procedure enables to achieve robust acoustic transparency and reduces the impact of comb-filtering artifacts. A comparison between single-and multi-loudspeaker equalization shows that for both cases a robust equalization performance can be achieved for different desired open ear transfer functions.

show abstract

Acoustic Equalization for Headphones Using a Fixed Feed-forward Filter

Cited by 8 publications

References 10 publications

In-Person or Virtual? – Assessing the Impact of COVID-19 on the Teaching Habits of Voice Pedagogues

In-Person or Virtual? – Assessing the Impact of COVID-19 on the Teaching Habits of Voice Pedagogues

Individualized sound pressure equalization in hearing devices exploiting an electro-acoustic model

Robust single- and multi-loudspeaker least-squares-based equalization for hearing devices

Contact Info

Product

Resources

About