Investigation on Audio Algorithms Architecture for Stereo Portable Devices

Cecchi, Stefania; Virgulti, Marco; Primavera, Andrea; al., et

doi:10.17743/jaes.2015.0084

Cited by 6 publications

(5 citation statements)

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“…On the one hand, there are methods that aim to improve the audio quality from loudspeakers incorporated into mobile devices. Such methods include low-frequency enhancement [4,25], spatialisation [4,6], dialogue clarity improvement [5], dynamics processing [5,25] and linearisation of frequency response [4,5,25]. These methods attempt to compensate for the constraints of the devices themselves and, with the exception of [5], do not aim to account for the listening environment.…”

Section: Audio Adaptation For Mobile Listeningmentioning

confidence: 99%

Exploring object-based content adaptation for mobile audio

Walton

Evans²,

Kirk

et al. 2018

Pers Ubiquit Comput

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Mobile devices enable users to consume media with audio content in a wide range of contexts, with environmental noise being present in many of these. Several methods exist that aim to improve the experience of mobile listening by utilising information about the environmental noise, such as volume and dynamic range adaptation. This paper explores a fundamentally different approach to improving the mobile listening experience by using the object-based audio paradigm, where individual audio sources are mixed in response to each specific listening context. Three experimental studies, containing both quantitative and qualitative aspects, are presented which investigate whether environmental noise influences preference of background-foreground audio object balance in a mix. The results indicate that environmental noise can influence the preferred audio mix and that the nature of the adaptations made is dependent upon both audio content and user. Additionally, qualitative analysis provides an understanding of the role of environmental noise on preferred audio mix. It is believed that the content adaptation method explored in this paper is a simple yet useful tool for adapting content to suit both the context and the user.

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Section: Audio Adaptation For Mobile Listeningmentioning

confidence: 99%

Exploring object-based content adaptation for mobile audio

Walton

Evans²,

Kirk

et al. 2018

Pers Ubiquit Comput

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“…Most of the research mentioned is applied to mono signals only. An audio algorithms architecture for stereo portable devices was proposed based on a spatializer in the context of small and very close loudspeakers that has a poor spatial sound image [19]. The results showed that the spatializer was proficient of enhancing the spatial impression.…”

Section: E Lpc Based Compressionmentioning

confidence: 99%

Audio Compression using a Modified Vector Quantization algorithm for Mastering Applications

Prince,

Kirubaraj

et al. 2022

International Journal of Electronics and Telecommunications

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Audio data compression is used to reduce the transmission bandwidth and storage requirements of audio data. It is the second stage in the audio mastering process with audio equalization being the first stage. Compression algorithms such as BSAC, MP3 and AAC are used as standards in this paper. The challenge faced in audio compression is compressing the signal at low bit rates. The previous algorithms which work well at low bit rates cannot be dominant at higher bit rates and vice-versa. This paper proposes an altered form of vector quantization algorithm which produces a scalable bit stream which has a number of fine layers of audio fidelity. This modified form of the vector quantization algorithm is used to generate a perceptually audio coder which is scalable and uses the quantization and encoding stages which are responsible for the psychoacoustic and arithmetical terminations that are actually detached as practically all the data detached during the prediction phases at the encoder side is supplemented towards the audio signal at decoder stage. Therefore, clearly the quantization phase which is modified to produce a bit stream which is scalable. This modified algorithm works well at both lower and higher bit rates. Subjective evaluations were done by audio professionals using the MUSHRA test and the mean normalized scores at various bit rates was noted and compared with the previous algorithms.

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“…This situation can be partially improved taking into consideration the acoustics of these devices and applying advanced audio techniques. In [275], a multi-point equalization procedure is introduced to improve the non-ideal response of a portable system such as the mobile phone. Objective measurements and subjective listening test results have confirmed the positive effect of the algorithms on personal portable devices.…”

Section: Portable Devicesmentioning

confidence: 99%

Room Response Equalization—A Review

2017

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Room response equalization aims at improving the sound reproduction in rooms by applying advanced digital signal processing techniques to design an equalizer on the basis of one or more measurements of the room response. This topic has been intensively studied in the last 40 years, resulting in a number of effective techniques facing different aspects of the problem. This review paper aims at giving an overview of the existing methods following their historical evolution, and discussing pros and cons of each approach with relation to the room characteristics, as well as instrumental and perceptual measures. The review is concluded by a discussion on emerging topics and new trends. This paper aims to provide an up-to-date review on RRE, discussing the pros and the cons of each technique, following the historical evolution. It is worth underlining that the RRE problem is analyzed from the viewpoint of impulse response analysis. All approaches that are not directly based on RIR analysis (e.g., parametric or graphic equalizers) are not discussed. The reader is referred to [11] for a comprehensive review on this topic. Another research field related to RRE which is not addressed in this paper is sound spatialization. The reader is referred to [12] for a recent review.This review article is organized as follows: Section 2 describes the characteristics of room impulse responses and its perception by the human auditory system. Section 3 introduces the basic concept of RRE, explaining the main challenges in inverting room responses. Section 4 describes the approaches used for equalizer design following their historical evolution. Section 5 discusses pre-processing techniques used to cope for RIR variations by exploiting human perception. Section 6 covers the evolution from single-point to multi-point equalization using multiple microphones placed within the room. Section 7 reports adaptive approaches for RRE in the framework of single-point and multi-point equalization. Section 8 introduces innovative approaches following a wave-theoretical view on the problem. Section 9 describes instrumental and perceptual measures used for state-of-the-art evaluation of RRE approaches. Section 10 reports emerging methods and new trends in the field. Finally, Section 11 concludes this review. The Room Response and Its PerceptionThe characteristics of the room response in the time and frequency domain are related to the acoustic properties of the environment that influence human perception. Due to this aspect, it is sensible to shape the impulse response analysis in order to handle important issues that should be considered in the RRE procedure to reach a sound listening improvement. This includes knowledge on human perception and psychoacoustics to be exploited explicitly in the equalization procedure. Appl. Sci. 2018, 8, 16 4 of 47An impulse response, obtained from a sound source in a specific position of a real environment, can be divided into three parts [13]: (i) direct sound; (ii) early reflections, and (iii) late reflections, as r...

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Investigation on Audio Algorithms Architecture for Stereo Portable Devices

Cited by 6 publications

References 0 publications

Exploring object-based content adaptation for mobile audio

Exploring object-based content adaptation for mobile audio

Audio Compression using a Modified Vector Quantization algorithm for Mastering Applications

Room Response Equalization—A Review

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