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copied!<p>I don't think the concept of "minimum sample value" is very meaningful, since the sample value just represents the current "height" of the sound wave at a certain time instant. I.e. its absolute value will vary between the peak value of the audio clip and zero. Thus, having a <code>targetRangeMin</code> seems to be wrong and will probably cause some distortion of the waveform.</p> <p>I think a better approach might be to have some sort of weight function that decreases the sample value based on its size. I.e. bigger values are decreased by a large percentage than smaller values. This would also introduce some distortion, but probably not very noticeable. </p> <p>Edit: here is a sample implementation of such a method:</p> <pre><code>public short normalize(short value) { short rawMax = // max from step1 short targetMax = 8000; //This is the maximum volume reduction double maxReduce = 1 - targetMax/(double)rawMax; int abs = Math.abs(value); double factor = (maxReduce * abs/(double)rawMax); return (short) Math.round((1 - factor) * value); } </code></pre> <p>For reference, this is what your algorithm did to a sine curve with an amplitude of 10000: <img src="https://i.stack.imgur.com/0Jsg9.png" alt="Original algorithm"></p> <p>This explains why the audio quality becomes much worse after being normalized.</p> <p>This is the result after running with my suggested <code>normalize</code> method: <img src="https://i.stack.imgur.com/1gDgc.png" alt="Suggested algorithm"></p>

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