Develop Reference

How to match text to audio in Python?

I have an audio file and a text that corresponds to the speech in this audio file.
Is there any way to match the text to the audio so that I get something like timestamps that show where the words in the text file appear in the audio.

So I have found exactly what I was looking for.
Apparently the technology that matches a given Text to an Audio and returns the exact timestamps is called Forced Alignment.
Here is an extremely useful link to a list of the best forced alignment tools: https://github.com/pettarin/forced-alignment-tools
Personally, I have used Aeneas as it worked really well for me.

Yes, that is possible. I am assuming you are aware of basic terminology around the audio tech.
Check library https://www.geeksforgeeks.org/python-speech-recognition-on-large-audio-files/
The library can read any audio file chunk by chunk. One could pass the file for audio to text conversion and further can collect the result of text chunk by chunk.
Also, If the SampleRate of the Audio File is 44100, then 8192 chunks will represent a time unit around 185 milliseconds.

Converting raw binary into Spectrogram

I have been searching and reading the approach of representing raw binaries or executable to a Spectrogram figure in Python. The thing I found was representing an already audio file, as .wav, into spectrogram
(https://fairyonice.github.io/implement-the-spectrogram-from-scratch-in-python.html)
(https://pythontic.com/visualization/signals/spectrogram)
My understanding that any file in my computer is a list of 0's and 1's. So if I want to represent an executable as a spectrogram, it is important first to define the sampling rate and bit depth. I was thinking of having 8000 samples/second as a sample rate and each sample is 1 byte. Then, we can represent the generated wave signal and the spectrogram.
Please let me know if I am misunderstanding anything.

Return type of wavfile.read in python

I need to analyse a sound file, in order to get when the sound is louder.
I have this :
rate, data = wavfile.read('test.wav')
I know the meaning of the rate value, but what really is in the data variable ?
It works well when I want to retrieve the time intervals of the louder part of the audio, by looking at the data list, but I can't really find out the meaning of this list...
Thank you very much

data holds a numpy array representing the sound in your .wav file.
Some good explanations on how the sound is represented in that data can be found in the following question:
What do the bytes in a .wav file represent?

data in wav files is audio samples. Most of the time it's 16bit signed integers. For wav files you mostly care about rate (sound frequency) and number of channels (if your wav file is not mono).

Reading raw audio values from ADC chip on raspberry pi

I wired up the MCP3008 ADC chip to an Electret Microphone and to my pi. I'm reading the input using bit-banging in python, and I'm getting an integer from 0-1024.
I followed this tutorial to do the bit-banging: https://learn.adafruit.com/reading-a-analog-in-and-controlling-audio-volume-with-the-raspberry-pi/connecting-the-cobbler-to-a-mcp3008
My question is how do I take this integer and convert it to something meaningful? Can I somehow write these bytes to a file in python to get the raw audio data that Audacity can play? Right now when I try to write the values they just show up as the integer instead of binary. I'm really new to python, and I've found this link for converting the raw data, but I'm having trouble generating the raw data first:Python open raw audio data file
I'm not even sure what these values represent, are they PCM data that I have to do math with related to time?

What you are doing here is sampling a time-varying analogue signal. so yes, the values you obtain are PCM - but with a huge caveat (see below). If you write them as a WAV file (possibly using this to help you), you will be able to open them in Audacity. You could either convert the values to unsigned 8-bit (by truncation and) or to 16-bit signed with a shift and subtraction.
The caveat is that PCM is the modulation of a sample clock with the signal. The clock signal in your case is the frequency with which you bit-bang the ADC.
Practically, it is very difficult to arrange for this to be regular in software - and particularly when bit-banging the device from a high-level language such as Python. You need to sample at twice the bandwidth of the signal (Nyquist's law) - so realistically, 8kHz for telephone speech quality.
An irregular sample clock will also result in significant artefacts - which you will hear as distortion.

How do you read this .wav file byte data?

I used the python wave module and read the first frame from a .wav file and it returned this :
b'\x00\x00\x00\x00\x00\x00'
What does each byte mean and will it be the same for every frame or for just some?
I've done some research into the subject and have found that there are bytes that give information about the .wav file in front of the sound data, so does python miss out this information and skip straight to the sound data or do I have to manually separate it?
There are 2 channels and a sample width of 3 according to python.
UPDATE
I have successfully created the waveform for the wav file, it wasn't as difficult as I first thought, now to show it whilst the song is playing....

The wave module reads the header for you, which is why it can tell you how many channels there are, and what the sample width is.
Reading frames gives you direct access to the raw sample data, but because the WAV format is a bit of a mixed, confused beast it depends on the sample width and channel count how you need to interpret each frame. See this article for a good in-depth discussion on that.