In this paper we look into the test methods to evaluate the quality of audio separation algorithms. Specifically we try to correlate the results of listening tests with stateofthe-art objective measures. To this end, the quality of the harmonic signals obtained with two harmonic-percussive separation algorithms was evaluated with BSS Eval, PEASS and via listening tests. A correlation analysis was conducted and results show that for harmonic-percussive separation algorithms, neither BSS Eval nor PEASS show strong correlation with the ratings obtained via listening tests and suggest that existing perceptual objective measures for quality assessment do not generalize well to different separation algorithms
Background: Loneliness and social isolation in older age are considered major public health concerns and research on technology-based solutions is growing rapidly. This scoping review of reviews aims to summarize the communication technologies (CTs) (review question RQ1), theoretical frameworks (RQ2), study designs (RQ3), and positive effects of technology use (RQ4) present in the research field. Methods: A comprehensive multi-disciplinary, multi-database literature search was conducted. Identified reviews were analyzed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. A total of N = 28 research reviews that cover 248 primary studies spanning 50 years were included. Results: The majority of the included reviews addressed general internet and computer use (82% each) (RQ1). Of the 28 reviews, only one (4%) worked with a theoretical framework (RQ2) and 26 (93%) covered primary studies with quantitative-experimental designs (RQ3). The positive effects of technology use were shown in 55% of the outcome measures for loneliness and 44% of the outcome measures for social isolation (RQ4). Conclusion: While research reviews show that CTs can reduce loneliness and social isolation in older people, causal evidence is limited and insights on innovative technologies such as augmented reality systems are scarce.
Perceptual coding of high quality digital audio signals or in short "audio compression" is one of the basic technologies of the multimedia age. This chapter introduces the basic ideas of perceptual audio coding and discusses the different options for the main building blocks of a perceptual coder. Several well known algorithms are described in detail.
Optimum Coding in the Frequency domain (OCF) uses entropy coding of quantized spectral coefficients to efficiently code high quality sound signals with 3 bits/sample.In an iterative algorithm psychoacoustic weigthing is used to get the quantization noise to be masked in every critical band. The coder itself uses iterative quantizer control to get each data block to be coded with a fixed number of bits.Details about the OCF-Coder are presented together with information about the codebook needed and the training for the entropy coder.An algorithm for calculating a noise-to-mask ratio is presented which helps to identify, where quantization noise could be audible.
WHY MUSIC CODING?New applications for the digital transmission and/or storage of sound signals require a smaller data rate than is standard today (compact disc: 16 bit uniform quantizer at 4 4 .
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