### Install pyAudioAnalysis Library and Dependencies Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/README.md Instructions to set up the pyAudioAnalysis library by cloning the repository and installing its required dependencies using pip. This prepares the environment for using the library's functionalities. ```Shell git clone https://github.com/tyiannak/pyAudioAnalysis.git pip install -r ./requirements.txt pip install -e . ``` -------------------------------- ### Run Comprehensive PyAudioAnalysis Library Tests Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/tests/README.md This Python command executes a comprehensive test suite to verify the core functionality and stability of the PyAudioAnalysis library. It's used to ensure the current version is working as expected after changes or installations. ```Python python3 script_tests.py ``` -------------------------------- ### Extract Audio Spectrogram via Command Line Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/README.md This command-line example illustrates how to use the `audioAnalysis.py` script to extract the spectrogram of an audio signal stored in a WAV file. It provides a quick way to perform basic audio analysis tasks directly from the terminal. ```Shell python audioAnalysis.py fileSpectrogram -i data/doremi.wav ``` -------------------------------- ### Train and Classify Audio Segments with pyAudioAnalysis Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/README.md This Python example demonstrates how to train an audio segment classifier using WAV files organized by class folders. After training, the model is used to classify an unknown audio WAV file, showcasing the library's classification capabilities. ```Python from pyAudioAnalysis import audioTrainTest as aT aT.extract_features_and_train(["classifierData/music","classifierData/speech"], 1.0, 1.0, aT.shortTermWindow, aT.shortTermStep, "svm", "svmSMtemp", False) aT.file_classification("data/doremi.wav", "svmSMtemp","svm") ``` -------------------------------- ### Deploy Trained PyAudioAnalysis Models Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/tests/README.md These shell commands copy the newly trained audio classification models from the local `models` directory to the PyAudioAnalysis library's data models folder and a specified research data directory. This step is necessary to make the trained models available for use by the library. ```Shell cp models/* ../pyAudioAnalysis/data/models/ cp models/* ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/models ``` -------------------------------- ### D3.js Chord Diagram Implementation for Similarity Visualization Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/pyAudioAnalysis/data/similarities.html Implements an interactive D3.js chord diagram to visualize relationships and similarities. It initializes the SVG canvas, loads data from 'Names.csv' and 'matrix.json', computes the chord layout, and renders interactive arcs and chords with mouseover titles and fading effects. ```JavaScript var width = 900, height = 900, outerRadius = Math.min(width, height) / 2 - 150, // make a bit smaller so that text doesn't crop innerRadius = outerRadius - 10; var formatPercent = d3.format(".1f%"); var arc = d3.svg.arc() .innerRadius(innerRadius) .outerRadius(outerRadius); var layout = d3.layout.chord() .padding(.04) .sortSubgroups(d3.descending) .sortChords(d3.ascending); var path = d3.svg.chord() .radius(innerRadius); var svg = d3.select("body").append("svg") .attr("width", width) .attr("height", height) .append("g") .attr("id", "circle") .attr("transform", "translate(" + (width / 2) + "," + (height / 2) + ")"); // leave some more slack svg.append("circle") .attr("r", outerRadius); d3.csv("Names.csv", function(cities) { d3.json("matrix.json", function(matrix) { // Compute the chord layout. layout.matrix(matrix); // Add a group per neighborhood. var group = svg.selectAll(".group") .data(layout.groups) .enter().append("g") .attr("class", "group") .on("mouseover", mouseover); // Add a mouseover title. group.append("title").text(function(d, i) { return cities[i].name + ": " + formatPercent(d.value) + " "; }); // Add the group arc. var groupPath = group.append("path") .attr("id", function(d, i) { return "group" + i; }) .attr("d", arc) .style("fill", function(d, i) { return cities[i].color; }); // Add a text label. /* var groupText = group.append("text") .attr("x", 6) .attr("dy", 15); groupText.append("textPath") .attr("xlink:href", function(d, i) { return "#group" + i; }) .text(function(d, i) { if (cities[i].name.split(" ---").length > 1) return cities[i].name.split(" ---")[1]; else return cities[i].name; }); // Remove the labels that don't fit. :( groupText.filter(function(d, i) { return groupPath[0][i].getTotalLength() / 2 - 16 < this.getComputedTextLength(); }) .remove(); */ var groupText = group.append("text") .each(function(d) { d.angle = 0.5 * (d.startAngle + d.endAngle); // The angle of the label }) .attr("dy", "1em") // ... or anything really .attr("transform", function(d) { return "rotate(" + (d.angle*180 / Math.PI - 90) + ")" + // rotate the text according to the angle "translate(" + (outerRadius + 10) + ")" + // move it outside the graph (d.angle > Math.PI ? "rotate(180)" : ""); // make readable }) .style("text-anchor", function(d) { return d.angle > Math.PI ? "end" : null; // make readable pt. II }) .text(function(d, i) { // name same as previously if (cities[i].name.split(" ---").length > 1) return cities[i].name.split(" ---")[1]; else return cities[i].name; }); // Add the chords. var chord = svg.selectAll(".chord") .data(layout.chords) .enter().append("path") .attr("class", "chord") .style("fill", function(d) { return cities[d.source.index].color; }) .attr("d", path); // Add an elaborate mouseover title for each chord. chord.append("title").text(function(d) { return cities[d.source.index].name + " → " + cities[d.target.index].name + ": " + formatPercent(d.source.value) + "\n" + cities[d.target.index].name + " → " + cities[d.source.index].name + ": " + formatPercent(d.target.value); }); function mouseover(d, i) { chord.classed("fade", function(p) { return p.source.index != i && p.target.index != i; }); } }); }); ``` -------------------------------- ### Execute Specific PyAudioAnalysis Shell Test Scripts Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/tests/README.md These shell commands allow for running individual, targeted tests for the PyAudioAnalysis library. Each script focuses on a particular aspect of the library's features, often requiring a path to the audio dataset as an argument for execution. ```Shell sh cmd_test_00.sh ../ sh cmd_test_01.sh ../ sh cmd_test_02.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_02_B.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_02_C.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_03.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_04.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_05.sh ../ sh cmd_test_06.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_07.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_08.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_09.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_10.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_11.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_12_1.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_12_2.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ sh cmd_test_12_3.sh ~/ResearchData/Audio\ Dataset/pyAudioAnalysisData/ ``` -------------------------------- ### BibTeX Citation for pyAudioAnalysis Library Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/README.md This snippet provides the recommended BibTeX format for citing the pyAudioAnalysis library in academic research work. It includes details such as the title, author, journal, volume, number, year, and publisher, ensuring proper attribution for the open-source library. ```BibTeX @article{giannakopoulos2015pyaudioanalysis, title={pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis}, author={Giannakopoulos, Theodoros}, journal={PloS one}, volume={10}, number={12}, year={2015}, publisher={Public Library of Science} } ``` -------------------------------- ### CSS Styling for D3.js Chord Diagram Elements Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/pyAudioAnalysis/data/similarities.html Provides foundational CSS rules for a D3.js chord diagram. It defines styles for the main circle, group paths, and individual chords, including a hover effect that hides unrelated chords to highlight connections. ```CSS @import url(style.css); #circle circle { fill: none; pointer-events: all; } .group path { fill-opacity: .5; } path.chord { stroke: #000; stroke-width: .25px; } #circle:hover path.fade { display: none; } ``` -------------------------------- ### Train PyAudioAnalysis Classifiers (SVM, k-NN) Source: https://github.com/tyiannak/pyaudioanalysis/blob/master/tests/README.md This Python script trains various audio classification models, including SVM with RBF kernel and k-Nearest Neighbors, for different audio analysis tasks. It requires a dataset directory and allows specifying the classifier type and the target task (e.g., speaker gender, music genre). ```Python python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t sm python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t movie8 python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t speakers python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t speaker-gender python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t music-genre6 python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c svm_rbf -t 4class python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t sm python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t movie8 python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t speakers python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t speaker-gender python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t music-genre6 python3 script_train_classifiers_all.py -d "/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/" -c knn -t 4class ``` === COMPLETE CONTENT === This response contains all available snippets from this library. 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