Audacity is an excellent audio application which can show a real time spectrogram of your input audio file sonic-visualiser is another essential audio tool for this purpose they will confirm what a proper spectrogram of your audio should look like to understand how to code up one I suggest you invest time understanding the notion of a fourier transform just slogging on some
Now that we have our mp3_to_text function defined, we can use it to convert MP3 files to text: filename = "audio.mp3" text = mp3_to_text (filename) print (text) This will convert the MP3 file audio.mp3 to text and print it to the console. You can also save the text to a file by writing it to a file instead of printing it: filename = "audio.mp3However, after obtained a numpy array using wav *= 32767 / max(0.01, np.max(np.abs(wav))), I want to convert it to a .mp3 file so that it will be easier to send it back as streaming response. Right now, I can convert .wav bytes object to a .mp3 file, but the problem is that I don't know how to convert the numpy array to a .wav bytes object. Step 3: Create the text-to-speech conversion function. Now we’re ready to create our text-to-speech conversion function. This function will take a string of text as input and return an audio I need to record a .3gp audio file coming from the Android front-end to be converted into .wav audio using the python Flask server back-end for further processing. Any suggested method or library to convert .3gp audio into .wav audio format? 1SwJiDq.