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Audio, or in terms of signal processing, an audio signal is an analog or digital representation of sound, typically as an electrical voltage.

1
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To find level mismatches between speech & SFX, you may first need to identify where there is speech and look at loudness & spectral power. Look at the Harmonic Product Spectrum (HPS) as an inexpensi …
answered Jan 27 '15 by ruoho ruotsi
2
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You have to have use some basic music theory to know "how to harmonize middle-C". For example, if you play a G4 and E4, you will be making a harmony with a basic 3-note chord (C-E-G). However, this is …
answered Nov 4 '14 by ruoho ruotsi
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I recommend looking at the open source music-analysis library called librosa, you can do tempo analysis in one line, on audio you've read into memory. …
answered Jan 9 '17 by ruoho ruotsi
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For python, I'd try out: pydub for basic audio manipulation and arrangement (slicing, concatenation, fading, repeating, etc). … There are also fantastic python audio libraries like librosa, in case you do decide to do any feature extraction or audio analysis. Good luck! …
answered Aug 17 '15 by ruoho ruotsi
2
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Have a good read of various features that can be extracted from popular audio analysis libraries like librosa: https://librosa.github.io/librosa/feature.html Fundamental frequency (F0) can definitely … But this would be a lot of processing as the concept of a "phone" in a speaker-independent sense is quite far from raw audio features one might compute directly on the audio signal (like RMS, ZCR, spectral …
answered Jan 9 '17 by ruoho ruotsi
1
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This means that from one spoken utterance to another, the way a speaker pronounces the same passphrase & the environmental/background noise impacts adds a bit of variance to the captured audio signal. …
answered Mar 28 '17 by ruoho ruotsi
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"Center" isn't the word that I'd use to describe what you want to do. Your signal does not have a zero-mean, so like @Dole suggested you should use a DC-Blocker (DC-Offset removing) filter to get the …
answered Dec 30 '15 by ruoho ruotsi
2
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Your question is really quite broad. In a nutshell, if you think of the "successive differences", called spectral flux, understood per frequency range you can start to generalize to different kinds …
answered Nov 29 '16 by ruoho ruotsi
0
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examples: https://stackoverflow.com/questions/27264156/sox-batch-process-under-debian https://pwnetics.wordpress.com/2011/07/12/bash-one-liner-using-sox-to-batch-convert-the-sampling-frequency-of-audio-files …
answered Dec 28 '15 by ruoho ruotsi
4
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From the KVR forum link above, dig in from this section: a Tape or Bucket Brigade Delay is better emulated using a fixed delayline with a variable sampling-rate. Classic digital delays typically mod …
answered Aug 18 '15 by ruoho ruotsi
3
votes
Maximal variance in spectral flatness can be observed in white noise (versus minimal variance in flatness from a pure sine tone). So white noise is your answer and yes, you can generate that in Audaci …
answered May 27 '15 by ruoho ruotsi
0
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If you're an absolute beginner, I recommend you start with a practical example (that you can see/hear). This will give you some "hands-on" experience before diving into papers. I highly recommend li …
answered Nov 12 '14 by ruoho ruotsi
1
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A cursory search of google will give you frequency response plots of various windows, for example: http://www.labbookpages.co.uk/audio/firWindowing.html …
answered Nov 29 '16 by ruoho ruotsi
1
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If you're doing ANY audio signal processing in python, I heartily recommend librosa. Your scipy route will work (read as float, process, playback), but it is less direct. …
answered May 26 '15 by ruoho ruotsi
1
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What you want to do is timbre recognition.
answered Aug 16 '15 by ruoho ruotsi

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