Reproduce An Experiment: The Problem And Its Importance

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QUESTION #1: THE PROBLEM AND ITS IMPORTANCE
The selected peer reviewed article is, “Design of database for evaluating 3D audio core algorithms” authored by Kang et al. (2016). The experimental study sought to solve the manual execution of conventional DBMS that are used in the assessment of audio systems given that most audio sources remain unindexed. The experiment proposed 3D audio architecture for analyzing the 3D audio core algorithm based on a database management system (DBMS). The experiment uses 3D sound sources, particularly in the separation of sound source algorithms. The experiment performs two important algorithms, namely separation and crosstalk cancellation. Sound source localization has been used to estimate sound sources using the acoustic signal output, besides simulation of separate instruments within a 3D virtual environment (Kang et al., 2016). This experiment is important as it proposes an automated system of evaluating 3D audio outputs to replace the conventional DB based systems that are manually executed due to lack of indexing technology for audio sources. Automating 3D audio evaluation process is important as it helps in cross talk elimination which necessitates the separation of single acoustic instruments and voices from a set of mixed acoustic signals (Kang et al., 2016). Secondly, the use of artificial reverberation is essential as it helps in the addition of a reverberation factor to audio recording besides playing an important role in the modification of diverse acoustic dimensions. Still, localization of the sound source is pivotal in the estimation of sound sources based on acoustic signal characteristics.
The problem: The conventional audio DB are performed independently through a manual search thus limiting the use of multiple audio sources besides causing inefficiencies as the conventional audio sources remain largely unindexed (Kang et al., 2016). Based on the research literature, it is still unclear as to whether the problem is agreed upon given that it's only one year since the publication of the study, hence only a handful of peer reviews have been received.
Proposed Solution: The experiment proposes a DB architecture that is capable of analyzing 3D audio and XML metadata algorithms.
QUESTION #2: STUDY RATIONALE AND LITERATURE LINK
The study is located within the literature. Though the authors made an effort to explore similar past experiments, the literature review is non-exhaustive and lacks depth. Though relevant sources have been used, the author failed to establish a research gap within the literature and linking it to the experiment. Nevertheless, the study is located within research literature and has satisfactorily accomplished the experimental objectives. The conclusion suggests that the aims of the study were attained as it concludes by affirming that a 3D audio core algorithm was developed based on a DBMS architecture that supports automatic assessment of core audio algorithms (Kang et al., 2016). However, the downside of the experiment is that it largely relied on a predefined algorithm which could hinder the generalization of the study results as there is no guarantee of consistency in across other algorithms. Nevertheless, the experiment achieved all of its objectives.
QUESTION #3: METHODOLOGY OF THE STUDY
The study utilized an experimental research methodology. This methodology was appropriate given that it involved manipulation of predefined experimental variables that include 3D audio core algorithms (Kang et al., 2016). Experimental methodology was appropriate given that the study was meant to provide a new solution to an existing problem.
QUESTION #4: RESULTS AND CONTRIBUTION TO KNOWLEDGE
A 3D audio database was developed for the analysis of 3D audio core algorithms. The 3D audio database relied on a DBMS that had automated capabilities, thus necessitating automatic evaluation of audio sources (Kang et al., 2016). The experiment evaluated the source separation algorithm since the author’s own database rather than the author’s own database. The study has made a significant contribution to the existing literature. It fills the existing gap on the subject of 3D audio evaluation DB systems specifically developed to evaluate the performance of modern 3D audio algorithms. In particular, the four audio core algorithms, namely audio localization, artificial reverberation, source separation and crosstalk cancellation had never been evaluated before (Kang et al., 2016). Most importantly, it is one of the first experiments to introduce automatic execution of 3D audio core algorithms. The study had made a departure from the conventional manual based audio algorithm evaluation techniques to automated 3D audio algorithm technology. Additionally, the study has made significant recommendations for future studies in this area. Since the experiment specifically evaluated the source separation algorithm, further research is required to evaluate similar 3D algorithms and in particular, localization...