I want to make the vibration wave to the audio file.
I can get the amplitude data from the .wav file. but Now i have a series amplitude data that's not from the .wav file. the data is as the following:
2013-02-12T02:58:00.047803 -1286
2013-02-12T02:58:00.097803 -1271
2013-02-12T02:58:00.147803 -1297
......
and so on ,200 datas per 1s.
How do i change the datas into the .wav files in python？
Use wave module in combination with pyaudio. I am not sure though if it lets you create file with 200hz sampling frequency. 200hz sampling frequency can contain only < 100 Hz frequencies . That's not even good for lowest piano key
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I've been using a bit of numpy and pysinewave to generate and analyse some sine waves and turn them into audio, but now that I have the audio I couldn't think of a way to detect the frequency or amplitude of the waves at some point of time, for example, I want to detect the amplitude of a wave in the audio in second one. Is there a way to do this in python with some library?
I tried trying to convert the audio files back into numpy to get the waves and try to sort of detect the amplitude every x seconds but I think my problem is way more simple to solve and I am overthinking it
I have an audio clip, and I want to detect when a certain (high pitch) noise occurs. I don't know anything about FFT, how do I return the audio frame at which the noise occurs (I was thinking frequency trigger)?
Since you already have "scipy" there: You can compute a spectrogram to get frequencies over time for your sample (which you can load with wavfile.read.
You can then plot the spectrogram and figure out what the frequency you're looking for is.
Then
either loop over the spectrogram data itself to find the time where there's suitably strong signal in that frequency, or
filter your original signal first (a bandpass filter would be best) and then find the overall intense bits.
how to divide a huge .wav file into multiple .wav files based on the labels marked in wave surfer like from this image
I want to divide wav files based on upper label values whenever 1 or 0 is seen till that it must be formed as one more .wav file
If you can't readily import that data into Python, you should check out the speaker diarization functions in the pyAudioAnalysis package.
I have audio recordings that starts and ends at different times.
audio 1: -----t1--------------------------s1->time
audio 2: ---------t2----s2------------------->time
audio 3: ------------------------t3-------s3->time
audio 1 is the longest and it overlaps with both audio 2 and 3.
audio 2, and audio 3 are short segments but they do not overlap at all.
Is there a python library that does this?
You could first use a python library to read the audio file (numpy or scipy for instance, see https://stackoverflow.com/a/26716031/3244382).
Then you have to determine t and s for each file. If the files are not too noisy a simple threshold on the audio signal could be sufficient. A little bit more sophisticated approach would be to compute the RMS energy or the envelope (that average the signal), and use a threshold on it.
Once you know s and t, you could write a new audio file from this boundaries with the same audio library.
I have a numpy array that represents audio data(dtype is np.int16). Here is a plot of the audio data(me saying "one, two"):
the sampling rate is 100HZ. I saved this array into a wav file. However, the wav file is not audible from other music players(iTunes, vlc, Audacity etc). It's just complete silence.
Here is how I saved the array:
scipy.io.wavfile.write('output.wav',100,waveform) # 'waveform' is the numpy array
I am wondering what could the cause be ?
sampling rate too low?
amplitude not enough ? i tried to normalize to -32767 to 32767, but still no sound
Any help is appreciated
PS:
This is how the file looks in Audacity(I'm not very familiar with this software):
With a sampling frequency of 100Hz the highest audible frequency you get is 50Hz.
The range of human hearing is from about 20 to about 20000Hz.
For "telephone quality" you need 8000Hz and for "cd quality" you need 44100Hz (that is the standard sampling frequency for consumer audio).