Hybrid in-car speech recognition for mobile multimedia applications

Kuhn, Thomas; Jameel, Abu Shafin Mohammad Mahdee; Stümpfle, Matthias; Haddadi, Afsaneh

doi:10.1109/vetec.1999.778396

Cited by 8 publications

(3 citation statements)

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“…Recent studies present contributions to identifying and optimizing vehicle interior noise [12][13][14][15][16][17], approaching different noise sources. The sound quality of the vehicle cabin is also essential for various in-vehicle applications, such as multimedia [18][19][20], security [21][22][23], assistive [24][25][26], and autonomous vehicles [27,28]. Furthermore, several studies in psychoacoustics seek to establish objective metrics to assess the subjective sound quality perceived by vehicle passengers [29,30], which is an essential factor for consumer satisfaction and the marketability of a vehicle [31].…”

Section: Related Workmentioning

confidence: 99%

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Flor

Pena

Oliveira

et al. 2022

Sensors

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Recently, the issue of sound quality inside vehicles has attracted interest from both researchers and industry alike due to health concerns and also to increase the appeal of vehicles to consumers. This work extends the analysis of interior acoustic noise inside a vehicle under several conditions by comparing measured power levels and two different models for acoustic noise, namely the Gaussian and the alpha-stable distributions. Noise samples were collected in a scenario with real traffic patterns using a measurement setup composed of a Raspberry Pi Board and a microphone strategically positioned. The analysis of the acquired data shows that the observed noise levels are higher when traffic conditions are good. Additionally, the interior noise presented considerable impulsiveness, which tends to be more severe when traffic is slower. Finally, our results suggest that noise sources related to the vehicle itself and its movement are the most relevant ones in the composition of the interior acoustic noise.

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Section: Related Workmentioning

confidence: 99%

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Flor

Pena

Oliveira

et al. 2022

Sensors

View full text Add to dashboard Cite

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“…Google Assistant [2], Apple's Siri or Amazon Alexa are nowadays relying on powerful cloud solutions for analysis and recognition of complex voice commands. While these systems are certainly useful, they rely on internet connection and are often used via Android Auto or Apple CarPlay [3]. They are also influenced by ambient noise, which has to be filtered out for proper command recognition.…”

Section: Introductionmentioning

confidence: 99%

Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition: The Possibilities of Next Generation 5G Data Networks

Martínek¹,

Baroš²,

Jaroš³

et al. 2022

Computers, Materials &Amp; Continua

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This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction. Modern vehicles are nowadays increasingly supporting voice commands, which are one of the pillars of autonomous and SMART vehicles. Robust speaker recognition for contextaware in-vehicle applications is limited to a certain extent by in-vehicle background noise. This article presents the new concept of a hybrid system, which is implemented as a virtual instrument. The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction. The study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks, which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual vehicles. On average, the unfiltered voice commands were successfully recognized in 29.34% of all scenarios, while the LMS reached up to 71.81%, and LMS-ICA hybrid improved the performance further to 73.03%.

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“…Acoustic noise has been considered a crucial issue and one of the most important topics in sensing and communication systems in vehicles in the last years. General vehicle applications depend on the audio signal quality such as multimedia [1][2][3][4], security [5][6][7][8][9], and assistive [10][11][12] and autonomous vehicle applications [13,14]. In addition, vehicle noise is a concern to researchers due to its effects on human health and comfort, both inside and outside the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Noise Level Inside a Vehicle under Different Conditions

Flor

Pena

et al. 2020

Sensors

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Vehicular acoustic noise evaluations are a concern of researchers due to health and comfort effects on humans and are fundamental for anyone interested in mitigating audio noise. This paper focuses on the evaluation of the noise level inside a vehicle by using statistical tools. First, an experimental setup was developed with microphones and a microcomputer located strategically on the car’s panel, and measurements were carried out with different conditions such as car window position, rain, traffic, and car speed. Regression analysis was performed to evaluate the similarity of the noise level from those conditions. Thus, we were able to discuss the relevance of the variables that contribute to the noise level inside a car. Finally, our results revealed that the car speed is strongly correlated to interior noise levels, suggesting the most relevant noise sources are in the vehicle itself.

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Hybrid in-car speech recognition for mobile multimedia applications

Cited by 8 publications

References 0 publications

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions

Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition: The Possibilities of Next Generation 5G Data Networks

Characterization of Noise Level Inside a Vehicle under Different Conditions

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