Mobile Communication Devices, Ambient Noise, and Acoustic Voice Measures

Maryn, Youri; Ysenbaert, Femke; Zarowski, Andrzej; Vanspauwen, Robby

doi:10.1016/j.jvoice.2016.07.023

Cited by 65 publications

(60 citation statements)

References 41 publications

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“…At higher external noise levels, the reliability slightly decreases, but it remains good. This result is qualitatively similar to that obtained by Maryn et al, 4 who used records of human patients with voice disorders. But in their work, these authors analyzed separately neither male and female voices, nor sustained vowels and continuous speech, nor the effects of different levels of voice alterations with regard to jitter and noise.…”

Section: Discussion the Icc And The Level Of Agreement Required For Csupporting

confidence: 91%

“…However, thanks to more efficient data compression techniques, higher audio quality can be achieved on smartphones with higher sampling rates and coding on 16, 24, and even 32 bits. This is again in line with the results of Maryn et al, 4 who emphasized the differences between devices, although these authors did not test cheap devices. Figure 7 illustrates the point with oscillograms of the same 3× /aiu/ utterance (200 Hz; N:H ratio = 0.46; jitter = 4.01%): the upper trace is the display of the direct signal by Praat (from computer to computer); the middle and bottom traces are the same signal recorded and transmitted by Smart1 and Smart2, respectively.…”

Section: Discussion the Icc And The Level Of Agreement Required For Csupporting

confidence: 89%

“…This is made possible by current smartphone technology (sound measurement applications or "apps"), although so far only some "apps" are really accurate. 3 As regards noise, very recently, Maryn et al 4 found that chains of dysphonic sustained vowels and continuous speech recorded by means of mobile communication devices (two tablet computers and three smartphones) were significantly impacted by ambient noise. They concluded that, due to combined differences in hardware, software, and ambient sound conditions, acoustic voice quality measures may differ between recording systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research

Lebacq¹,

Schoentgen

Cantarella

et al. 2017

Journal of Voice

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Summary: Purpose. Smartphone technology provides new opportunities for recording standardized voice samples of patients and transmitting the audio files to the voice laboratory. This drastically improves the achievement of baseline designs, used in research on efficiency of voice treatments. However, the basic requirement is the suitability of smartphones for recording and digitizing pathologic voices (mainly characterized by period perturbations and noise) without significant distortion. In a previous article, this was tested using realistic synthesized deviant voice samples (/a:/) with three precisely known levels of jitter and of noise in all combinations. High correlations were found between jitter and noise to harmonics ratio measured in (1) recordings via smartphones, (2) direct microphone recordings, and (3) sound files generated by the synthesizer. In the present work, similar experiments were performed (1) in the presence of increasing levels of ambient noise and (2) using synthetic deviant voice samples (/a:/) as well as synthetic voice material simulating a deviant short voiced utterance (/aiuaiuaiu/). Results. Ambient noise levels up to 50 dBA are acceptable. However, signal processing occurs in some smartphones, and this significantly affects estimates of jitter and noise to harmonics ratio when formant changes are introduced in analogy with running speech. The conclusion is that voice material must provisionally be limited to a sustained /a/.

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Section: Discussion the Icc And The Level Of Agreement Required For Csupporting

confidence: 91%

Section: Discussion the Icc And The Level Of Agreement Required For Csupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research

Lebacq¹,

Schoentgen

Cantarella

et al. 2017

Journal of Voice

View full text Add to dashboard Cite

show abstract

“…However, the effect of room acoustics and ambient noise becomes a significant issue that the current study did not address. Maryn et al (2017) investigated the combined effect of environmental noise and a variety of mobile recording devices on 10 acoustic parameters including all those used in this study. They found that only F0 was robust against both environmental noise and recording system.…”

Section: Discussionmentioning

confidence: 99%

Assessing voice health using smartphones: bias and random error of acoustic voice parameters captured by different smartphone types

Jannetts

Schaeffler

Beck

et al. 2019

Intl J Lang & Comm Disor

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Background Occupational voice problems constitute a serious public health issue with substantial financial and human consequences for society. Modern mobile technologies such as smartphones have the potential to enhance approaches to prevention and management of voice problems. This paper addresses an important aspect of smartphone‐assisted voice care: the reliability of smartphone‐based acoustic analysis for voice health state monitoring. Aim To assess the reliability of acoustic parameter extraction for a range of commonly used smartphones by comparison with studio recording equipment. Methods & Procedures Twenty‐two vocally healthy speakers (12 female, 10 male) were recorded producing sustained vowels and connected speech under studio conditions using a high‐quality studio microphone and an array of smartphones. For both types of utterance, Bland–Altman analysis was used to assess overall reliability for mean F0, cepstral peak prominence (CPPS), Jitter (RAP) and Shimmer %. Outcomes & Results Analysis of the systematic and random error indicated significant bias for CPPS across both sustained vowels and passage reading. Analysis of the random error of the devices indicated that that mean F0 and CPPS showed acceptable random error size, while jitter and shimmer random error was judged as problematic. Conclusions & Implications Confidence in the feasibility of smartphone‐based voice assessment is increased by the experimental finding of high levels of reliability for some clinically relevant acoustic parameters, while the use of other parameters is discouraged. We also challenge the practice of using statistical tests (e.g., t‐tests) for measurement reliability assessment.

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“…Furthmüller & Waldhorst (2012) explained that mobile devices ffer a set of resources in which we find sensors like GPS and accelerometer. Maryn, Ysenbaert, Zarowski, & Vanspauwen (2017) mentioned various built-in sensors carried by mobile devices such as a microphone, camera, GPS, accelerometer and light sensor.…”

Section: Context-awarenessmentioning

confidence: 99%

What is a smart device? - a conceptualisation within the paradigm of the internet of things

2018

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The Internet of Things (IoT) is an interconnected network of objects which range from simple sensors to smartphones and tablets; it is a relatively novel paradigm that has been rapidly gaining ground in the scenario of modern wireless telecommunications with an expected growth of 25 to 50 billion of connected devices for 2020 Due to the recent rise of this paradigm, authors across the literature use inconsistent terms to address the devices present in the IoT, such as mobile device, smart device, mobile technologies or mobile smart device. Based on the existing literature, this paper chooses the term smart device as a starting point towards the development of an appropriate definition for the devices present in the IoT. This investigation aims at exploring the concept and main features of smart devices as well as their role in the IoT. This paper follows a systematic approach for reviewing compendium of literature to explore the current research in this field. It has been identified smart devices as the primary objects interconnected in the network of IoT, having an essential role in this paradigm. The developed concept for defining smart device is based on three main features, namely context-awareness, autonomy and device connectivity. Other features such as mobility and userinteraction were highly mentioned in the literature, but were not considered because of the nature of the IoT as a network mainly oriented to device-to-device connectivity whether they are mobile or not and whether they interact with people or not. What emerges from this paper is a concept which can be used to homogenise the terminology used on further research in the Field of digitalisation and smart technologies.

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Mobile Communication Devices, Ambient Noise, and Acoustic Voice Measures

Cited by 65 publications

References 41 publications

Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research

Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research

Assessing voice health using smartphones: bias and random error of acoustic voice parameters captured by different smartphone types

What is a smart device? - a conceptualisation within the paradigm of the internet of things

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