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It's very hard to point you to relevant techniques without knowing any context for your problem. The obvious answer would be to tell you to adjust the gain of each sample so that clipping rarely occu …

First of all, how the data is encoded in a mp3 file is irrelevant to the question unless you aim at doing compressed-domain processing (which would be quite foolish). So you can assume your algorithm …

Its relationship to voice is only historical, and it is currently used for pitch-shifting and time-stretching in lower-end audio hardware/software. …

What you are trying to do has been tried over and over by hundreds of researchers and there is quite a large body of work about this. Check the proceedings of the ISMIR conference. Even if it is not u …

The closest example I can think of is the beginning of Suzanne Vega's "Tom's Diner" which has been used for the mpeg-1 layer 3 development, and is still occasionally used to demo audio codecs. …

\sum_k a_k z^{-k}}$, and is thus entirely characterized by the coefficients $a_k$ The principle of early LPC coders (such as LPC10) is thus to estimate these parameters from chunks of the incoming audio … Observe that in this process, nothing of the original audio samples is actually transmitted. …

Search for "speech/music segmentation" or "audio segmentation" and you'll find thousands of research papers. … Compute audio features on the first half, on the second half, and use a statistical test to decide which hypothesis is the most likely: the two sets of audio features are drawn from the same distribution …

Since the only information required to compute an output sample is the few past input/output samples, there is no problem to apply it to streaming audio. …

First, you will have to correct for differences in timing. For example, if one utterance is "--heeelloooo---" and the other "hellooooooo----" (- representing silence), a direct pairwise comparison of …

It looks like you are mixing up two techniques: MinBLEP and band-limited wavetables. Band-limited wavetables Let's assume you have a 256 sample long array with a waveform of interest - for example a …

Changing the volume of an audio signal must be done by applying a gain (multiplication) - and optionally clipping if your system has a limited dynamic range. This is as simple as that. … Applying a non-linear function to an audio signal will cause distortion and add harmonics, and you don't want this to happen - you want to modify the loudness of the signal, not its timbre. …

The task of taking a long contiguous audio recording and splitting it up in chunks in which only one speaker is speaking - without any prior knowledge about the voice characteristics of each speaker - …

Two remarks: I am assuming you are plotting the real (or imaginary) part of the Fourier transform. It is much more common to work with the magnitude or squared magnitude (power spectrum). The peak i …

When synthesizing and processing audio on modern processors, It will come down to what kind of synthesizing and processing you do. … Keep in mind that it is quite ridiculous to expect a hardware audio chain to have more than 20 bits of precision (assuming the board is impeccably routed and all parts are ideal, we're still running into …

I think that what confuses you is that a decreasing exponential ($e^{-x}$) does never reach 0, so an ADSR generator with truly exponential segments would stay stuck ; because it would never reach the …