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Perceptual audio coders are widely used when storage space or streaming bandwidth for audio content is limited. If the used bitrate is low, various coding artifacts can be introduced that degrade the perceived audio quality. A suite of algorithms has been developed to conceal these coding artifacts and to improve the perceived sound quality in automotive environments. This paper is a continuation of a previous paper and introduces two post-processing algorithms for restoring the spatial signal quality of decoded compressed audio signals. Both algorithms work single-ended, i.e. without access to the bitrate or other side information. The merit of the algorithms is demonstrated by listening tests. A second part of the paper describes algorithms that enhance the spatial image.
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For the first time since the invention of the automobile, self-driving cars are upending automotive audio. Four new forces; self-driving cars, people sitting anywhere in a car, the need for rapid layout configurability, and different ownership models will require something new to meet the audio need. The core of a new system will be a ‘phaseless’ way to generate spatial sound. Additionally, the ability to generate a fully discrete Center channel that appears before the listener, no matter where they are will be essential. Through mathematical formulas and future-sound layouts, this paper identifies the issues, trends and discusses the key capabilities that audio systems will need to deliver high quality sound to any listener location within a self-driving car.
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This paper addresses prediction techniques for evaluating the consequences of adding a grille assembly onto a loudspeaker. Numerical modeling is applied in order to assess the acoustical effects imposed on the loudspeaker sub-system defined as a loudspeaker, interface, and grille. Investigations are performed in a virtual infinite baffle scenario under semi-anechoic conditions, where various modeling aspects are included in the studies. The predictions are shown to accurately reproduce the prominent features of the sub-system when compared with experimental data. The paper highlights the intricacies of both measurement and correct modeling of the geometry of the parts and their acoustic properties – particularly at higher audio frequencies.
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This paper is a summary of acoustic measurement environments used for automotive microphones. Different environments are presented so that the right method can be found according to the microphones specification. The summary also shows why different measurement environments need to be used for the main types of microphones in automotive applications such as hands-free communication and active noise control.
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Paper describes the problems to be solved during the design, implementation and testing of Engine Order Cancellation systems (EOC). Special attention is drawn to the black-box tests using industrial computer for modeling the acoustical environment of the car, engine noises, CAN-signals and for evaluating the quality of the system. It is shown that using computer based tests allow detecting problems that either cannot or very hardly can be detected during in-car tests. Block diagram of the automated EOC test system is given. Comprehensive analysis of circumstances that can lead to the problems in EOC is done. Tests for their automatic detection are described.
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The presented active road noise control system uses multichannel reference signals provided by digital automotive accelerometer sensors strategically placed on suspension or chassis to predict the structure-born road noise transferred from the tires into the cabin. Omni-directional microphones installed in the vehicle roofline, close to the passenger’s ears, are used as error microphones. Once activated, the system is minimizing the road noise and establishing a quite zone in the proximity of these locations. Only the standard built-in vehicle loudspeakers are used as actuators. The presented digital audio amplifier platform compromise the complete multichannel control and update algorithm processing in parallel with an audio processing. Several road noise scenarios from different vehicles are used to indicate state-of-the-art road noise reduction performance.
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In recent years, the engine-sound control method has shifted from noise reduction to sound design. Therefore, we have proposed a method to design the engine sound using active sound quality control (ASQC) based on ANC technology. Specifically, we propose an algorithm for amplifying and reducing the engine-specific order components. In addition, the auditory impressions of engine sound controlled by ASQC were investigated using psychoacoustic measurements. The results indicated that the control corresponding to the individual is important for improvements in auditory impressions. So, ASQC was developed to adjust to individual preferences. The individual preferences were connected to each driver’s driving pattern using deep learning. Thus, we developed an ASQC system, which enables the automatic generation of individual sound preferences.
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Smart Audio is gaining more and more attention in broadcast and media production industry. The Smart Audio concept is to utilizing real time processing algorithms that are both intelligent and adaptive. Those algorithms are perfectly prepared to be used in car environment for automated adaptive loudness-based audio control. To attract and retain listeners, consistent, stable and coherent audio is a vital requirement. One aspect that is particularly important to pay attention to is speech intelligibility. This is most critical and difficult in a live car reproduction situation. The Poster will present some proofed solutions and use cases for Smart Audio Procedures in Car Environment.
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Perceptual audio coders are widely used when storage space or streaming bandwidth for audio content is limited. If the used bitrate is low, various coding artifacts can be introduced that degrade the perceived audio quality. A suite of algorithms has been developed to conceal these coding artifacts and to improve the perceived sound quality in automotive environments. This paper is a continuation of a previous paper and introduces two post-processing algorithms for restoring the spatial signal quality of decoded compressed audio signals. Both algorithms work single-ended, i.e.~without access to the bitrate or other side information. The merit of the algorithms is demonstrated by listening tests. A previous paper presents algorithms that enhance the timbral sound characteristics.
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This paper is the continuation of the study presented at the “AES Berlin 2017” convention regarding the main causes of scrap during the production of a midrange loudspeaker. Various samples with reference and modified components have been built and characterized in terms of frequency response, THD and lumped parameters. Also, a second set of samples has been built using reference components but varying the assembly process and these samples have been characterized as the previous ones. After measurements performed both in an anechoic chamber and in a production line, a new set of measurements has been done inside a production car, in order to check if the results obtained in the preceding study would have been confirmed by field measurements
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