Home Audio System Research Articles

Synthesis of soundfields through irregular loudspeaker arrays based on convolutional neural networks

Most soundfield synthesis approaches deal with extensive and regular loudspeaker arrays, which are often not suitable for home audio systems, due to physical space constraints. In this article, we propose a technique for soundfield synthesis through more easily deployable irregular loudspeaker arrays, i.e., where the spacing between loudspeakers is not constant, based on deep learning. The input are the driving signals obtained through a plane wave decomposition-based technique. While the considered driving signals are able to correctly reproduce the soundfield with a regular array, they show degraded performances when using irregular setups. Through a complex-valued convolutional neural network (CNN), we modify the driving signals in order to compensate the errors in the reproduction of the desired soundfield. Since no ground truth driving signals are available for the compensated ones, we train the model by calculating the loss between the desired soundfield at a number of control points and the one obtained through the driving signals estimated by the network. The proposed model must be retrained for each irregular loudspeaker array configuration. Numerical results show better reproduction accuracy with respect to the plane wave decomposition-based technique, pressure-matching approach, and linear optimizers for driving signal compensation.

Applying Affordance Factor Analysis for Smart Home Speakers in Different Age Groups: A Case Study Approach

Many people use smart speakers at home nowadays for various reasons, such as playing music, checking news and weather, setting timers/alarms, etc. However, before smart speakers were created and available on the market, people used to have home audio systems for similar applications. Nonetheless, the control systems of smart speakers have many different appearances. Affordance is the information given by an object, which is determined by its appearance and supplies clues about its appropriate operation. Therefore, smart speakers should have affordances. Since smart speakers are the main device in the sustainable lifestyle of human beings in smart homes, this study analyzed the affordances of its appearance affect people and the result is essential to the sustainability of smart home. The present study presents a review of the smart speakers in Taiwan, focusing on the four main affordances (physical, cognitive, sensory, functional) and three different age groups (60 participants) based on four appearance categories of smart speaker control, namely, mechanical button control, no-button–no-touch control, touchscreen control, and touch sensor control. By examining the comparison of three age groups, 18–24, 25–49 and 50+, the results of one-way ANOVA showed that the smart speakers with touchscreen control and touch sensor control had a significant difference (p < 0.01) in four main affordances among these three age groups. The smart speakers with mechanical button control and no-button–no-touch control had no significant difference (p > 0.01) in four main affordances among these three age groups. In conclusion, age-range and cultural group affect the affordance of smart home speakers.

Ranking Security of IoT-Based Smart Home Consumer Devices

Manufacturers of smart home consumer devices like home theatres, music players, voice-based assistants, smart lighting, and security cameras have widely adopted the Internet of Things (IoT). These devices pose a significant security risk to consumers because the devices are exposed to mobile applications and cloud-based services with known security vulnerabilities. Most current home consumer devices provide little or no information about the level of security they afford. Since most consumers are not tech-savvy, it is currently difficult for a consumer to make an informed decision about which consumer device model (e.g., smart television model) has the best security. Hence, consumers need an objective security ranking of each type (e.g., security cameras) of home consumer devices. This paper proposes a novel methodology to systematically build such security rankings for home consumer devices. The proposed methodology can be applied by utilizing data from any security assessment study. The paper discusses previous efforts in applying Analytic Hierarchy Process (AHP) to rank security risks in general. The paper also presents a systematic survey of security vulnerabilities of smart home consumer devices when viewed from an IoT lens. Using the proposed methodology, a case study, employing an AHP model for ranking commonly used home consumer devices including home theatres, security cameras, smart lighting, smart speakers, video surveillance, smart switches, home automation systems, home security systems, smart routers, wireless doorbell cameras, and home audio systems, was developed. Relative security rankings for each type of consumer device were derived from the AHP model. According to the AHP model, network security was the primary driver of smart home device security with a priority of 0.6893 while application security had the least priority of 0.0591. Critical Vulnerabilities were the most important for device security (priority=0.4397), Man-in-The-Middle attacks for network security (priority=0.2019), exploitable services for cloud security (priority=0.26), and sensitive data for application security (0.7626). The AHP model was internally consistent (Consistency Ratio < 0.1). Sensitivity analysis showed that the AHP model was robust against pairing assumptions.

Personalized smart home audio system with automatic music selection based on emotion

In this paper, we introduce a personalized home audio system that uses IoT technologies to recommend and play music remotely based on a user’s estimated emotion. This system estimates a user’s emotion based on texts on their smartphone collected during outdoor activities. Based on this emotion, our system then searches for music that matches it from a music database. The system automatically detects the user when they return home, and plays the recommended music via a connected audio system. Consequently, personalized emotion-based music recommendation is provided transparently without the user’s awareness.

Measurement of standby power for selected electrical appliances in Australia

High growth in the uptake of electrical appliances is accounting for a significant increase in electricity consumption globally. In some developed countries, standby energy alone may account for about 10% of residential electricity use. The standby power for many appliances used in Australia is still well above the national goal of 1 W or less. In this paper, field measurements taken of standby power and operating power for a range of electrical appliances are presented. It was found that the difference between minimum value and maximum value of standby power could be quite large, up to 22.13 W for home theatre systems, for example. With the exception of home audio systems, however, the annual operating energy used by most electrical appliances was generally greater than the annual standby energy. Consumer behaviour and product choice can have a significant impact on standby power and operating power, which influences both energy demand and greenhouse gas emissions.

Quality Enhancement of Compressed Audio Based on Statistical Conversion

Most audio compression formats are based on the idea of low bit rate transparent encoding. As these types of audio signals are starting to migrate from portable players with inexpensive headphones to higher quality home audio systems, it is becoming evident that higher bit rates may be required to maintain transparency. We propose a novel method that enhances low bit rate encoded audio segments by applying multiband audio resynthesis methods in a postprocessing stage. Our algorithm employs the highly flexible Generalized Gaussian mixture model which offers a more accurate representation of audio features than the Gaussian mixture model. A novel residual conversion technique is applied which proves to significantly improve the enhancement performance without excessive overhead. In addition, both cepstral and residual errors are dramatically decreased by a feature-alignment scheme that employs a sorting transformation. Some improvements regarding the quantization step are also described that enable us to further reduce the algorithm overhead. Signal enhancement examples are presented and the results show that the overhead size incurred by the algorithm is a fraction of the uncompressed signal size. Our results show that the resulting audio quality is comparable to that of a standard perceptual codec operating at approximately the same bit rate.

Horn loudspeakers for the home: Past, present, and future

At the start of recorded sound, acoustical horns were an integral part of early home audio. As electrical reproducers were developed, horns were still required because of electromechanical driver and amplifier limitations. In 1928, the wider bandwidth of the Rice–Kellogg direct radiator loudspeaker and availability of higher-power amplifiers all but removed the horn loudspeaker from home audio systems. After 1928, horn loudspeakers were only found in theater PA systems, until the introduction in the late ’40s of the Klipschorn, which spawned a revival of horn loudspeakers in the 1950s. The introduction of high-power solid-state amplifiers and small bookshelf speakers in the 1960s removed horns from home audio systems. In the early ’90s, the reintroduction of low-power class A tube amplifiers spurred a new interest in new horn designs. The new horn designs utilize the Tractrix horn contour for high frequencies and hyperbolic-exponential horn contours for the bass frequencies. Also, the new horn design efforts have removed colorations in the sound which plagued many of the vintage horn systems. Future horn systems will feature lighter diaphragms, better magnets, and (maybe) room temperature super conducting voice coils for higher efficiencies.

Method and equalization of home audio systems

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