We present an intelligent approach to multitrack dynamic range compression where all parameters are configured automatically based on side-chain feature extraction from the input signals. A method of adjustment experiment to explore how audio engineers set the ratio and threshold is described. We use multiple linear regression to model the relationship between different features and the experimental results. Parameter automations incorporate control assumptions based on this experiment and those derived from mixing literature and analysis. Subjective evaluation of the intelligent system is provided in the form of a multiple stimulus listening test where the system is compared against a no-compression mix, two human mixes, and an alternative approach. Results showed that mixes devised by our system are able to compete with or outperform manual mixes by semi-professionals under a variety of subjective criteria.
Software engineering education requires students to develop technical knowledge and advanced cognitive and behavioral skills, particularly in the transition from novice to proficient. In distance learning, the hurdles are greater because students require greater autonomy, adopting strategies of self and co-regulation of learning. Facing these challenges, the SimProgramming approach has been transposed into the context of DL: e-SimProgramming. In the second iteration of e-SimProgramming implementation (2019/2020), one adaptation was inclusion of metacognitive challenges (MC) to promote students' self-reflection on their learning process. We explain the design of the two types of implemented MCs. We provide qualitative and quantitative analysis of: 1) evolution of MCs submission throughout the semester, identifying regularity and completion within deadlines and their relationship to student success; 2) students' perceptions of MCs. Results show a positive correlation between high MC submission and student success, greater interest and involvement of students in type 2 MCs and positive perceptions of students about MCs.
It is a common belief that settings of artificial reverb and delay time in music production are strongly linked to musical tempo and related factors. But this relationship, if in existence, is not yet understood. We present the results of two subjective tests that evaluate user preference of young adults with formal training in audio engineering on artificial reverb and delay time, while trying to relate choice to tempo and other low-level explaining factors. Results show there is a conclusive relationship between musical tempo and delay time preference as described by users. Reverb time setting preference, however, cannot be explained in such a strong manner. In this latter aspect the present work has nevertheless uncovered some ideas on how to proceed in order to quantify the phenomenon. INTRODUCTIONThe current work consists of the analysis of two subjective tests, performed with knowledgable practitioners, that strive to explain the relationship between the choice for the time parameter in artificial temporal processing units and the underlying musical content. Specifically, we hypothesize, following technical literature [1,2], that there is a relationship between a song's musical tempo and the definition of artificial reverb and delay times.A delay, or echo, consists of a discrete repetition of the signal after a given period of time. This repetition can be individual or can have sequels, which are frequently (but not necessarily) evenly spaced in time. Below a delay time of about 30 ms, the human ear does not perceive a repetition, and it integrates both dry and delayed sounds, which means we will consider that the processing we call "delay" to consist of times that are greater than this interval.Artificial reverberation is a process that strives to emulate and complement the real phenomena of room reverberation. The physical manifestation of this effect depends upon the numerous reflections that spring from the room's boundaries creating a series of differently timed echoes that blend into a tail that will prolong the sound. It is typical to distinguish between early reflections (sparse and coloring) and reverberant sound (dense and statistically uncorrelated). It is reverberation that offers the sonic footprint that enables one to identify the sound of a room. One crucial parameter is the Reverberation Time (RT 60 ), which for historical reasons is given as the time it takes for the tail to decay 60 dB after the original sound has ceased to exist.In the following Section we will contextualize the current work, looking also into the reasons and possible applications, while highlighting its differences to previous approaches. In Sec. 2 we discuss the subjective test methodology and statistical approach that was common to both tests. In Sec. 3 we present and interpret the results and further comments by test subjects, leading to some post-hoc analysis in Sec. 4. Some tentative conclusions are drawn in Sec. 5, along with indications for future work. PRIOR WORK AND MOTIVATIONIn [3], 60 successful practicing so...
Logistic and Gompertz growth equations are the usual choice to model sustainable growth and immoderate growth causing depletion of resources, respectively. Observing that the logistic distribution is geo-max-stable and the Gompertz function is proportional to the Gumbel max-stable distribution, we investigate other models proportional to either geo-max-stable distributions (log-logistic and backward log-logistic) or to other max-stable distributions (Fréchet or max-Weibull). We show that the former arise when in the hyper-logistic Blumberg equation, connected to the Beta (p,q) function, we use fractional exponents p−1=1∓1/α and q−1=1±1/α, and the latter when in the hyper-Gompertz-Turner equation, the exponents of the logarithmic factor are real and eventually fractional. The use of a BetaBoop function establishes interesting connections to Probability Theory, Riemann–Liouville’s fractional integrals, higher-order monotonicity and convexity and generalized unimodality, and the logistic map paradigm inspires the investigation of the dynamics of the hyper-logistic and hyper-Gompertz maps.
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