Interesting solution! I'm surprised it can tell the diff between 6000 and 6001 hz, most audio devices run at fixed frequencies and most players don't bother correcting. Using your much-beloved sox utility on a fixed-rate raw file might give you more reliable and portable control -- resample it to one rate and force it to output at another rate.
:cool: after installing solaris 10 5/08/09 directory the computer rebooting then the massage "out of frequency" appear.i want a solution first
second my main board is GA-MA780G UD3H (14 Replies)
Hi,
Could anyone help me with the following question, if I have two colums (names and frequency) as follows in a file called name.txt
Michael 1
Jones 1
Ben 2
Rebeca 4
David 1
and I want to use bash script called freqnames.sh that takes one argument (name) and the output should be... (3 Replies)
IKHz_SW_OSX.py
A DEMO mono _pure_ sinewave generator using standard text mode Python 2.6.7 to at least 2.7.3.
This code is EASILY modifyable to Python version 3.x.x...
This DEMO kids level 1KHz generator is mainly for a MacBook Pro, (13 inch in my case), OSX 10.7.5 and above. See below...... (0 Replies)
A very simple crude sinewave generator.
The file required is generated inside the code, is linear interpolated and requires /dev/audio to work. Ensure you have this device, if not the download oss-compat from your OS's repository...
It lasts for about 8 seconds before exiting and saves a... (5 Replies)
I'm trying to record audio using Audacity 2.0.5 installed from SlackBuilds. My system is 64-bit Slackware 14.1 and a sound card is Intel HD Audio. I didn't change my sound system to OSS. (Default sound system in Slackware 14.1 is ALSA, isn't it?) First, I set Internal Microphone slider in KMix... (2 Replies)
This is a small program as a tester for a basic sweep generator for bandwidth testing of AudioScope.sh.
This DEMO is only capable of 4KHz down to about 85Hz and back due to the low bit rate, but it is proof of concept for a much wider variant using a much higher bit rate.
The file generated... (4 Replies)
Ok guys, gals and geeks...
As from today I am starting to learn awk in earnest doing something totally different.
I am going to create a pseudo-Audio_Function Generator centred around OSX 10.11.x minimum. The code below is a tester to see what the possibilities are.
All waveforms will be... (11 Replies)
Hi all...
Well I have not been inactive but working out how to make OSX 10.14.x command line audio player have a variable sample rate.
This is a back door as afplay does not have a sample rate flag unlike aplay for ALSA, in Linux flavours.
This is a DEMO only but a derivative of it will... (2 Replies)
Discussion started by: wisecracker
2 Replies
LEARN ABOUT DEBIAN
numm.spectral-analysis
spectral-analysis(7) Numm Tutorials spectral-analysis(7)NAME
spectral analysis - perform realtime spectral analysis
SYNOPSIS
numm-run FILE
DESCRIPTION
Frequency makes for a meaningful description of many audio signals. We can use numpy's fourier analysis to compute spectra from the micro-
phone and display the results visually. We will break down the process into smaller parts: baby steps...
First, create and save a skeletal file that moves a line across the screen:
idx = 0
def video_out(a):
global idx
a[:,idx] = 255
idx = (idx + 1) % a.shape[1]
def audio_in(a):
pass
Save this snippet and run it with numm-run.
We will use the numpy.fft module for our analysis. First we define a function to get a particular frequency from the fourier transform:
import numpy as np
def get_freq(fourier, frequency):
freqs = np.fft.fftfreq(len(fourier), 1/44100.0)
nearest = (abs(freqs - frequency)).argmin()
return abs(fourier[nearest])
Next, we hook up this function to audio input from the microphone. A frequency bin is chosen on a log scale for each row on the screen to
display a spectogram. In total:
import numpy as np
idx = 0
recent_audio = np.zeros(4096, np.int16)
recent_video = np.zeros((240,320,3), np.uint8)
freq_bins = np.exp2(np.linspace(np.log2(27000),np.log2(27),240))
def get_freq(fourier, frequency):
freqs = np.fft.fftfreq(len(fourier), 1/44100.0)
nearest = (abs(freqs - frequency)).argmin()
return abs(fourier[nearest])
def video_out(a):
global idx
fourier=np.fft.fft(recent_audio)
values =np.array([get_freq(fourier,X) for X in freq_bins])
recent_video[:,idx,1] = (values/10000).clip(0,255)
idx = (idx + 1) % a.shape[1]
a[:] = np.roll(recent_video, -idx, axis=1)
def audio_in(a):
recent_audio[:] = np.roll(recent_audio, len(a))
recent_audio[:len(a)] = a.mean(axis=1)
SEE ALSO numm-run(1), numm.getting-started(7), numm.one-bit-instrument(7)numm February 2012 spectral-analysis(7)