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copied!<p>First you will need to perform a system call to <code>sox</code>, and capture its output. For example:</p> <pre><code>> spam = system("sox worf.wav -n stat 2>&1", intern = TRUE) > spam [1] "Samples read: 34000" "Length (seconds): 3.083900" [3] "Scaled by: 2147483647.0" "Maximum amplitude: 0.999969" [5] "Minimum amplitude: -0.938721" "Midline amplitude: 0.030624" [7] "Mean norm: 0.190602" "Mean amplitude: -0.004302" [9] "RMS amplitude: 0.244978" "Maximum delta: 1.340240" [11] "Minimum delta: 0.000000" "Mean delta: 0.051444" [13] "RMS delta: 0.099933" "Rough frequency: 715" [15] "Volume adjustment: 1.000" </code></pre> <p>Setting <code>intern = TRUE</code> returns the output of the command to a variable. Strangely, <code>sox</code> provides its output to <code>stderr</code> and not <code>stdout</code>, hence the need for <code>2>&1</code>. The best way forward now is to wrap this in a function which also postprocesses the output of <code>system</code>:</p> <pre><code>get_wav_stats = function(wav_file) { rough_wav_stats = system(sprintf("sox %s -n stat 2>&1", wav_file), intern = TRUE) wav_stats = data.frame(do.call("rbind", strsplit(rough_wav_stats, split = ":"))) names(wav_stats) = c("variable", "value") wav_stats = transform(wav_stats, value = as.numeric(as.character(value))) return(wav_stats) } > spam = get_wav_stats("worf.wav") > spam variable value 1 Samples read 3.400000e+04 2 Length (seconds) 3.083900e+00 3 Scaled by 2.147484e+09 4 Maximum amplitude 9.999690e-01 5 Minimum amplitude -9.387210e-01 6 Midline amplitude 3.062400e-02 7 Mean norm 1.906020e-01 8 Mean amplitude -4.302000e-03 9 RMS amplitude 2.449780e-01 10 Maximum delta 1.340240e+00 11 Minimum delta 0.000000e+00 12 Mean delta 5.144400e-02 13 RMS delta 9.993300e-02 14 Rough frequency 7.150000e+02 15 Volume adjustment 1.000000e+00 </code></pre> <p>Next you can wrap this in an apply loop to get all the stats from a given directory:</p> <pre><code># files_dir = list.files("path", full.names = TRUE) # For this example I create a mock list: files_dir = rep("worf.wav", 10) stat_wavs = lapply(files_dir, get_wav_stats) > str(stat_wavs) List of 10 $ :'data.frame': 15 obs. of 2 variables: ..$ variable: Factor w/ 15 levels "Length (seconds)",..: 13 1 14 2 8 7 6 4 10 3 ... ..$ value : num [1:15] 3.40e+04 3.08 2.15e+09 1.00 -9.39e-01 ... $ :'data.frame': 15 obs. of 2 variables: ..$ variable: Factor w/ 15 levels "Length (seconds)",..: 13 1 14 2 8 7 6 4 10 3 ... ..$ value : num [1:15] 3.40e+04 3.08 2.15e+09 1.00 -9.39e-01 ... << snip >> $ :'data.frame': 15 obs. of 2 variables: ..$ variable: Factor w/ 15 levels "Length (seconds)",..: 13 1 14 2 8 7 6 4 10 3 ... ..$ value : num [1:15] 3.40e+04 3.08 2.15e+09 1.00 -9.39e-01 ... </code></pre> <p>To extract only the <code>value</code> column, which contains the stats you need:</p> <pre><code>stats4files = data.frame(do.call("rbind", lapply(stat_wavs, "[[", 2))) names(stats4files) = stat_wavs[[1]][[1]] rownames(stats4files) = files_dir # this doesn't work actually because I have repeated the same file multiple times :) > stats4files Samples read Length (seconds) Scaled by Maximum amplitude Minimum amplitude Midline amplitude 1 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 2 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 3 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 4 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 5 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 6 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 7 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 8 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 9 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 10 34000 3.0839 2147483647 0.999969 -0.938721 0.030624 Mean norm Mean amplitude RMS amplitude Maximum delta Minimum delta Mean delta 1 0.190602 -0.004302 0.244978 1.34024 0 0.051444 2 0.190602 -0.004302 0.244978 1.34024 0 0.051444 3 0.190602 -0.004302 0.244978 1.34024 0 0.051444 4 0.190602 -0.004302 0.244978 1.34024 0 0.051444 5 0.190602 -0.004302 0.244978 1.34024 0 0.051444 6 0.190602 -0.004302 0.244978 1.34024 0 0.051444 7 0.190602 -0.004302 0.244978 1.34024 0 0.051444 8 0.190602 -0.004302 0.244978 1.34024 0 0.051444 9 0.190602 -0.004302 0.244978 1.34024 0 0.051444 10 0.190602 -0.004302 0.244978 1.34024 0 0.051444 RMS delta Rough frequency Volume adjustment 1 0.099933 715 1 2 0.099933 715 1 3 0.099933 715 1 4 0.099933 715 1 5 0.099933 715 1 6 0.099933 715 1 7 0.099933 715 1 8 0.099933 715 1 9 0.099933 715 1 10 0.099933 715 1 </code></pre>

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