Noise | Acoustics.org

2pNS8 – Noise Dependent Coherence-Super Gaussian based Dual Microphone Speech Enhancement for Hearing Aid Application using Smartphone

Nikhil Shankar– nxs162330@utdallas.edu
Gautam Shreedhar Bhat – gxs160730@utdallas.edu
Chandan K A Reddy – cxk131330@utdallas.edu
Dr. Issa M S Panahi – imp015000@utdallas.edu
Statistical Signal Processing Laboratory (SSPRL)
The University of Texas at Dallas
800W Campbell Road,
Richardson, TX – 75080, USA

Popular Version of Paper 2pNS8, “Noise dependent coherence-super Gaussian based dual microphone speech enhancement for hearing aid application using smartphone” will be presented Tuesday afternoon, May 8, 2018, 3:25 – 3:40 PM, NICOLLET D3
175th ASA Meeting, Minneapolis

Records by National Institute on Deafness and Other Communication Disorders (NIDCD) indicate that nearly 15% of adults (37million) aged 18 and over report some kind of hearing loss in the United States. Amongst the entire world population, 360 million people suffer from hearing loss.

Over the past decade, researchers have developed many feasible solutions for hearing impaired in the form of Hearing Aid Devices (HADs) and Cochlear Implants (CI). However, the performance of the HADs degrade in the presence of different types of background noise and lacks the computational power, due to the design constraints and to handle obligatory signal processing algorithms. Lately, HADs manufacturers are using a pen or a necklace as an external microphone to capture speech and transmit the signal and data by wire or wirelessly to HADs. The expense of these existing auxiliary devices poses as a limitation. An alternative solution is the use of smartphone which can capture the noisy speech data using the two microphones, perform complex computations using the Speech Enhancement algorithm and transmit the enhanced speech to the HADs.

In this work, the coherence between speech and noise signals [1] is used to obtain a Speech Enhancement (SE) gain function, in combination with a Super Gaussian Joint Maximum a Posteriori (SGJMAP) [2,3] single microphone SE gain function. The weighted union of these two gain functions strikes a balance between noise suppression and speech distortion. The theory behind the coherence method is that the speech from the two microphones is correlated, while the noise is uncorrelated with speech. The block diagram of the proposed method is as shown in Figure 1.

Fig. 1. Block diagram of proposed SE method.

For the objective measure of quality of speech, we use Perceptual Evaluation of Speech Quality (PESQ). Coherence Speech Intelligibility Index (CSII) is used to measure the intelligibility of speech. PESQ ranges between 0.5 and 4, with 4 being high speech quality. CSII ranges between 0 and 1, with 1 being high intelligibility. Figure 2 shows the plots of PESQ and CSII versus SNR for two noise types, and performance comparison of proposed SE method with the conventional Coherence and LogMMSE SE methods.

Fig.2. Objective measures of speech quality and intelligibility

Along with Objective measures, we perform Mean Opinion Score (MOS) tests on 20 normal hearing both male and female subjects. Subjective test results are shown in Figure 3, which illustrates the effectiveness of the proposed method in various background noise.

Fig. 3. Subjective test results

Please refer our lab website https://www.utdallas.edu/ssprl/hearing-aid-project/ for video demos and the sample audio files are as attached below.

Audios: Audio files go here:

Noisy

Enhanced

Key References:
[1] N. Yousefian and P. Loizou, “A Dual-Microphone Speech Enhancement algorithm based on the Coherence Function,” IEEE Trans. Audio, Speech, and Lang. Processing, vol. 20, no.2, pp. 599-609, Feb 2012.
[2] Lotter, P. Vary, “Speech Enhancement by MAP Spectral Amplitude Estimation using a super-gaussian speech model,” EURASIP Journal on Applied Sig. Process, pp. 1110-1126, 2005.
[3] C. Karadagur Ananda Reddy, N. Shankar, G. Shreedhar Bhat, R. Charan and I. Panahi, “An Individualized Super-Gaussian Single Microphone Speech Enhancement for Hearing Aid Users With Smartphone as an Assistive Device,” in IEEE Signal Processing Letters, vol. 24, no. 11, pp. 1601-1605, Nov. 2017.

*This work was supported by the National Institute of the Deafness and Other Communication Disorders (NIDCD) of the National Institutes of Health (NIH) under the grant number 5R01DC015430-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The authors are with the Statistical Signal Processing Research Laboratory (SSPRL), Department of Electrical and Computer Engineering, The University of Texas at Dallas.

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1aNS3 – Low-frequency sound control by means of bio-inspired and fractal designs

Anastasiia O. Krushynska – akrushynska@gmail.com
Federico Bosia – fbosia@unito.it
Nicola M. Pugno – nicola.pugno@unitn.it
Laboratory of Bio-inspired and Graphene Nanomechanics
Department of Civil, Environmental and Mechanical Engineering
Uiversity of Trento
Via Mesiano 77
Trento, 38123, ITALY

Popular version of paper 1aNS3, “Fractal and bio-inspired labyrinthine acoustic metamaterials”
Presented Monday morning, May 7, 2018, 9:15-9:35, Nicolett 3D
175th ASA Meeting, Minneapolis

Road, rail, airports, industry, urban environments, crowds – all generate high-volume sound. When sound becomes uncomfortable or even painful to the ear, it is generally called noise. Nowadays, noise is one of the most widespread environmental problems in developed countries, negatively affecting public health and quality of life. Recent findings of the World Health Organization show that noise pollution is not only annoying for a large percentage of the population, but also causes sleep disturbance, increases the risk of cardiovascular diseases, intensifies the level of stress and hinders learning processes. Low-frequency noise is the most troublesome type and is mainly produced by road vehicles, aircraft, industrial machinery, wind turbines, compressors, air-conditioning units, etc.

The attenuation or elimination of low-frequency noise is a challenging task due to its numerous sources, its ability to bypass obstacles, and the limited efficiency of most sound barriers. The laws of acoustics tell us that if a solid wall is used to attenuate noise, sound transmission is inversely proportional to its mass per unit area and the sound frequency. This means that very heavy walls, more than ten meters thick (!), are necessary to efficiently reduce typical low-frequency noise in the frequency range between 10 and 1000 Hz.

Fortunately, modern technology can provide more innovative and efficient solutions, based on so-called acoustic metamaterials. These are engineered structures capable of effectively slowing down sound speed and reducing sound intensity thanks to enhanced internal structural losses. The latter can be induced by incorporating internal resonators, which transfer mechanical vibrational energy into heat, or by using a geometry-related mechanism, exploiting the artificial elongation of sound propagation paths by means of narrow, so-called “labyrinthine” channels. In this work, we develop labyrinthine acoustic metamaterials with long narrow channels inspired by the structure of spider webs or arranged along fractal space-filling curves. These particular designs help to extend the metamaterial functionalities as compared to simpler configurations analyzed in previous years.

What happens if a sound wave enters a straight narrow channel? Depending on the channel geometry, it can either propagate through it, or be attenuated. For narrow channels, friction effects in the vicinity of the channel walls hinder wave propagation, and can eventually lead to its total attenuation. For moderately wide channels, if the sound wavelength matches the distance between the two channel edges (i.e., it equals an integer number of half wavelengths), resonance takes place, allowing to amplify the sound transmission. Both the described effects take place at single frequencies.

But what happens if the channels are arranged in the shape of a maze or if there is a set of coiled channels? We now know that for certain configurations, other types of collective resonances can be induced – Mie resonances – that enable the achievement of total reflection at rather wide frequency ranges.

We have found out that natural spider-web designs for the channel labyrinths provide sufficient freedom for the development of metamaterials with switch on/off regimes between total transmission and total reflection that can be easily adapted for controlling low-frequency sound. In particular, we have shown that a light-weight re-configurable structure with a square cross section of 0.81 m² is capable of totally reflecting airborne sound at frequencies of 50-100 Hz and above [1]. Moreover, by modifying the channel thickness and length, we can tune operating frequencies to desired ranges. In fact, the proposed metamaterials provide exceptional versatility for application in low-frequency sound control and noise abatement.

Incorporation of more advanced designs, e.g. coiling wave paths along space-filling curves, enables to develop more compact configurations and opens a route for creating efficient sound absorbers [2]. Space-filling curves are lines constructed by an infinite iterative process with the aim to fill in a certain area, e.g. a square or cube. Since the work of G. Peano (1890) until the 1980s, these curves were considered no more than mathematical curiosities, and only recently have they found application in fields like data science and routing systems. The use of space-filling curves for wave path labyrinths in combination with the added effect of friction in narrow channels has allowed us to achieve total reflection or to improve wave absorption of low-frequency sound. The absorption can be increased up to 100 % at selected frequencies, if a hybrid configuration with incorporated Helmholtz resonators is used [3]. This could be the next chapter to be written in the story of efficient noise abatement through innovative metamaterials.

$fractal$

[1] A.O. Krushynska, F. Bosia, M. Miniaci and N. M. Pugno, “Spider web-structured labyrinthine acoustic metamaterials for low-frequency sound control,” New J. Phys., vol. 19, pp. 105001, 2017.

[2] A.O. Krushynska, F. Bosia, and N. M. Pugno, “Labyrinthine acoustic metamaterials with space-coiling channels for low-frequency sounf control,” Acta Acust.united Ac., vol. 104, pp. 200–210, 2018.

[3] A.O. Krushynska, V. Romero-García, F. Bosia, N.M. Pugno, J.P. Groby, “Extra-thin metamaterials with space-coiling designs for perfect sound absorption”, (working paper), 2018.

2aNSa1 – Tranquillity Trails in the city?

Greg Watts – g.r.watts@bradford.ac.uk
Faculty of Engineering and Informatics
University of Bradford
Bradford
West Yorkshire
UK
BD7 1DP

Popular version of 2aNSa1. Tranquillity in the city—Building resilience through identifying, designing, promoting, and linking restorative outdoor
environments
Presented at the 173rd ASA Meeting
Boston, Massachusetts
June 2017

Tranquil spaces can be found and made in the city, and their promotion and use by residents and visitors is an important means of building resilience. Studies have shown that spaces rated by visitors as tranquil are more likely to produce higher levels of relaxation and less anxiety that should ultimately result in health and well-being benefits.

Such spaces can therefore be classed as restorative environments. Tranquil spaces are characterized by a soundscape dominated by natural sounds and low levels of man-made noise. In addition, the presence of vegetation and wild life has been shown to be an important contributory factor. Levels of rated tranquillity can be reliably predicted using a previously developed model called TRAPT, and then used it to design and identify tranquil spaces, improve existing green spaces and develop Tranquillity Trails to encourage usage.

Tranquillity Trails are walking routes designed to enable residents and visitors to reflect and recover from stress while receiving the benefits of healthy exercise. This paper describes Tranquillity Trails designed for three contrasting areas. Predictions of the rated tranquillity have been made along these routes and feedback from users was elicited at one site that confirmed the expected benefits.

The aim is to design a route that starts near the center, is simple and safe to follow and will allow users to experience a relatively degree of tranquility despite being in an urban area. Clearly the challenge is greater in a city with higher concentrations of people and traffic than for a town. The first three TTs designed are in Bradford, Kingsbridge and Guildford. These are all in England, though further ones are currently being develop in the US, Ireland and Hong Kong.

Below is an example of a Tranquillity Trail leaflet for Guildford, a large town in the UK. It is folded into three panels for ease of handling. A pdf file of the leaflet can be downloaded from: http://www.guildford.gov.uk/visitguildford/CHttpHandler.ashx?id=21855&p=0

In addition, an app for a smart mobile devices describing interesting features of this route together with a map and cursor showing current position is freely available from: http://www.handheldtours.co.uk/

Effects of noise for workers in the transportation industry

Marion Burgess m.burgess@adfa.edu.au
Brett Molesworth b.molesworth@unsw.edu.au

University of New South Wales, Australia

Popular version of paper
Presented June 28, 2017, in session 4aNSa, Measuring, Modeling, and Managing Transportation Noise I. 8:00 AM – 12:20 PM
173rd ASA Meeting, Boston

There are well established limits for workplace noise based on the risk of hearing damage. For example, an 8-hour noise exposure level is limited to 85 decibels (when the sound is this loud you need to shout to talk to someone near you). There are also guidelines for acceptable noise levels in workplaces that aim to ensure the noise will not be intrusive or affect the ability of the worker to do the tasks. For example, a design level for a general office may be 40 to 45 decibels (dBA), while for a ticket sales area, 45 to 50 dBA. In this range, noise should not have an adverse affect on your ability to complete a task.

However, there are many work environments, particularly in the transportation industry, in which the noise levels are above 50 dBA but the employees are required to perform tasks that require a high level of concentration and attention. For pilots and bus, truck and train drivers, the noise levels in the area they are working can be 65 to more than 75 dBA at times.

These workers all need to make safety-critical decisions and operate technical equipment in the presence of continuous noise generated from their vehicle’s engine. Transport check-in staff need to communicate and process passengers in noisy check-in halls where there is both vehicle and equipment noise as well as the noise from personnel around, such as “babble.”

In this paper, we discuss findings from a number of studies investigating the effect of constant noise at 65 dBA on various cognitive and memory skills. Two noise sources were used: One, a wideband noise like constant mechanical noise from an engine, and the other a babble noise of multiple persons’ incomprehensible speech. Language background is another factor that can increase cognitive load for those workers who are communicating in a language that is not native.

The cognitive tasks aimed to test working memory with an alphabet span test and recognition memory using a cued recall task. The signal to noise ratio used was 0, -5 and -10 dBA. Wideband noise was found to have a greater effect on working memory and recognition memory than babble noise.
Those who were not native English speakers were also more affected by the wideband noise than the babble noise. The subjective assessment, when the subjects were asked their opinion of the effect of the noise and the annoyance, was also greater for broadband noise.

These findings reinforce the limitations of basing acceptability on a simple overall dBA value alone. The reduction in performance demonstrates the importance of reducing the noise levels within transportation workplaces.

2aNS – How virtual reality technologies can enable better soundscape design

W.M. To – wmto@ipm.edu.mo
Macao Polytechnic Institute, Macao SAR, China.
A. Chung – ac@smartcitymakter.com
Smart City Maker, Denmark.
B. Schulte-Fortkamp – b.schulte-fortkamp@tu-berlin.de
Technische Universität Berlin, Berlin, Germany.

Popular version of paper 2aNS, “How virtual reality technologies can enable better soundscape design”
Presented Tuesday morning, November 29, 2016
172nd ASA Meeting, Honolulu

The quality of life including good sound quality has been sought by community members as part of the smart city initiative. While many governments have placed special attention to waste management, air and water pollution, acoustic environment in cities has been directed toward the control of noise, in particular, transportation noise. Governments that care about the tranquility in cities rely primarily on setting the so-called acceptable noise levels i.e. just quantities for compliance and improvement [1]. Sound quality is most often ignored. Recently, the International Organization for Standardization (ISO) released the standard on soundscape [2]. However, sound quality is a subjective matter and depends heavily on the perception of humans in different contexts [3]. For example, China’s public parks are well known to be rather noisy in the morning due to the activities of boisterous amateur musicians and dancers – many of them are retirees and housewives – or “Da Ma” [4]. These activities would cause numerous complaints if they would happen in other parts of the world, but in China it is part of everyday life.

According to the ISO soundscape guideline, people can use sound walks, questionnaire surveys, and even lab tests to determine sound quality during a soundscape design process [3]. With the advance of virtual reality technologies, we believe that the current technology enables us to create an application that immerses designers and stakeholders in the community to perceive and compare changes in sound quality and to provide feedback on different soundscape designs. An app has been developed specifically for this purpose. Figure 1 shows a simulated environment in which a student or visitor arrives the school’s campus, walks through the lawn, passes a multifunctional court, and get into an open area with table tennis tables. She or he can experience different ambient sounds and can click an object to increase or decrease the volume of sound from that object. After hearing sounds at different locations from different sources, the person can evaluate the level of acoustic comfort at each location and express their feelings toward overall soundscape. She or he can rate the sonic environment based on its degree of perceived loudness and its level of pleasantness using a 5-point scale from 1 = ‘heard nothing/not at all pleasant’ to 5 = ‘very loud/pleasant’. Besides, she or he shall describe the acoustic environment and soundscape using free words because of the multi-dimensional nature of sonic environment.

Figure 1. A simulated soundwalk in a school campus.

To, W. M., Mak, C. M., and Chung, W. L.. Are the noise levels acceptable in a built environment like Hong Kong? Noise and Health, 2015. 17(79): 429-439.
ISO. ISO 12913-1:2014 Acoustics – Soundscape – Part 1: Definition and Conceptual Framework, Geneva: International Organization for Standardization, 2014.
Kang, J. and Schulte-Fortkamp, B. (Eds.). Soundscape and the Built Environment, CRC Press, 2016.
Buckley, C. and Wu, A. In China, the ‘Noisiest Park in the World’ Tries to Tone Down Rowdy Retirees, NYTimes.com, from http://www.nytimes.com/2016/07/04/world/asia/china-chengdu-park-noise.html , 2016.

1aNS5 – Noise, vibration, and harshness (NVH) of smartphones

Inman Jang – kgpbjim@yonsei.ac.kr
Tae-Young Park – pty0948@yonsei.ac.kr
Won-Suk Ohm – ohm@yonsei.ac.kr
Yonsei University
50, Yonsei-ro, Seodaemun-gu
Seoul 03722
Korea

Heungkil Park – heungkil.park@samsung.com
Samsung Electro Mechanics Co., Ltd.
150, Maeyeong-ro, Yeongtong-gu
Suwon-si, Gyeonggi-do 16674
Korea

Popular version of paper 1aNS5, “Controlling smartphone vibration and noise”
Presented Monday morning, November 28, 2016
172nd ASA Meeting, Honolulu

Noise, vibration, and harshness, also known as NVH, refers to the comprehensive engineering of noise and vibration of a device through stages of their production, transmission, and human perception. NVH is a primary concern in car and home appliance industries because many consumers take into account the quality of noise when making buying decisions. For example, a car that sounds too quiet (unsafe) or too loud (uncomfortable) is a definite turnoff. That said, a smartphone may strike you as an acoustically innocuous device (unless you are not a big fan of Metallica ringtones), for which the application of NVH seems unwarranted. After all, who would expect the roar of a Harley from a smartphone? But think again. Albeit small in amplitude (less than 30 dB), smartphones emit an audible buzz that, because of the close proximity to the ear, can degrade the call quality and cause annoyance.

Figure 1: Smartphone noise caused by MLCCs

The major culprit for the smartphone noise is the collective vibration of tiny electronics components, known as multi-layered ceramic capacitors (MLCCs). An MLCC is basically a condenser made of piezoelectric ceramics, which expands and contracts upon the application of voltage (hence piezoelectric). A typical smartphone has a few hundred MLCCs soldered to the circuit board inside. The almost simultaneous pulsations of these MLCCs are transmitted to and amplified by the circuit board, the vibration of which eventually produces the distinct buzzing noise as shown in Fig. 1. (Imagine a couple hundred rambunctious little kids jumping up and down on a floor almost in unison!) The problem has been even more exacerbated by the recent trend in which the name of the game is “The slimmer the better”; because a slimmer circuit board is much easier to flex it transmits and produces more vibration and noise.

Recently, Yonsei University and Samsung Electromechanics in South Korea joined forces to address this problem. Their comprehensive NVH regime includes the visualization of smartphone noise and vibration (transmission), the identification and replacement of the most problematic MLCCs (production), and the evaluation of harshness of the smartphone noise (human perception). For visualization of smartphone noise, a technique known as the nearfield acoustic holography is used to produce a sound map as shown in Fig. 2, in which the spatial distribution of sound pressure, acoustic intensity or surface velocity can be overlapped on the snapshot of the smartphone. Such sound maps help smartphone designers draw a detailed mental picture of what is going on acoustically and proceed to rectify the problem by identifying the groups of MLCCs most responsible for producing the vibration of the circuit board. Then, engineers can take corrective actions by replacing the (cheap) problematic MLCCs with (expensive) low-vibration MLCCs. Lastly, the outcome of the noise/vibration engineering is measured not only in terms of physical attributes such as sound pressure level, but also in their psychological correlates such as loudness and the overall psychoacoustic annoyance. This three-pronged strategy (addressing production, transmission, and human perception) is proven to be highly effective, and currently Samsung Electromechanics is offering the NVH service to a number of major smartphone vendors around the world.

Figure 2: Sound map of a smartphone surface

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