I need to calculate amplitude of the audio from a video streaming source which is in .asf format in PYTHON. Currently, I have tried to convert it into .wav file and used wave python package but I need to do it in real time. In short, need to perform following steps;
Continously read input video stream
Pre processing the audio signal
Calculate amplitude in given interval
Currentl used wave library of python and read the stored wav format clip, then extracted the amplitude from the wave.readframes() output such that
wf = wave.open()
data = wf.readframes()
amplitude = data[2]
Related
I need to extract audio stream from a video and check whether it has any pitch changes or abnormalities. Ideally, we want to quantify any pitch changes in the audio stream. I'm aware that I can use ffmpeg to extract the audio stream from the video. However, what tools or programs (python?) can then be used to identify and quantify any pitch changes or abnormalities in the audio stream?
Pitch analysis is not an easy task, luckily there are existing solutions for that. https://pypi.org/project/crepe/ is an example that looks promising.
You could read the resulting CSV of pitch data into a Pandas dataframe and perform whatever data analysis you can think of.
For example for the pitch change analysis you could do
df['pitch_change'] = df.frequency.diff(periods=1)
To get a column representing the pitch change of every time unit.
I have an audio file that lasts 294 seconds (sampling rate is 50000). I use torchaudio to compute its spectrogram the following way:
T.MelSpectrogram(sample_rate=50000, n_fft=1024, hop_length=512)
Say, there is an important event in the original .wav audio at second 57 exactly. How can I determine exactly what pixel that event will start at on the spectrogram.
Or, put simply, how can I map a moment in an audio to a location in a spectrogram?
How would i convert a wave file to an image in such a way that i can recover the original wave file from the image, in python please.
I have heard of wav2vec library but its not clear from the documentation how i would convert the vector back into a wave.
ggg=[]
for wav in os.listdir('/content/drive/My Drive/New folder'):
fs, data = wavfile.read(wav)
ggg.append(data)`
I would like to append instead the image as i am creating a data-set to train an algorithm on. After completing training, the algorithm will generate images from the same distribution that another piece of code should convert to a wave file.
I have just started to work on data in the form of audio. I am using librosa as a tool. My project requires me to extract features like:
Total duration of the audio
Minimum Intensity of the audio signal
Maximum Intensity of the audio signal
Mean Intensity of the audio signal
Jitter
Rate of speaking
Number of Pauses
Maximum Duration of Pauses
Average Duration of Pauses
Total Duration of Pauses
Although, I know about these terms but I have no idea how to extract these from an audio file. Are these inbuilt in some form in the librosa.feature variable? Or we need to manually calculate these? Can someone guide me how to proceed?
I know that this job can be performed using softwares like Praat, but I need to do it in python.
Praat can be used for spectral analysis (spectrograms), pitch
analysis, formant analysis, intensity analysis, jitter, shimmer, and
voice breaks.
I have an mp3 file and I want to basically plot the amplitude spectrum present in that audio sample.
I know that we can do this very easily if we have a wav file. There are lot of python packages available for handling wav file format. However, I do not want to convert the file into wav format then store it and then use it.
What I am trying to achieve is to get the amplitude of an mp3 file directly and even if I have to convert it into wav format, the script should do it on air during runtime without actually storing the file in the database.
I know we can convert the file like follows:
from pydub import AudioSegment
sound = AudioSegment.from_mp3("test.mp3")
sound.export("temp.wav", format="wav")
and it creates the temp.wav which it supposed to but can we just use the content without storing the actual file?
MP3 is encoded wave (+ tags and other stuff). All you need to do is decode it using MP3 decoder. Decoder will give you whole audio data you need for further processing.
How to decode mp3? I am shocked there are so few available tools for Python. Although I found a good one in this question. It's called pydub and I hope I can use a sample snippet from author (I updated it with more info from wiki):
from pydub import AudioSegment
sound = AudioSegment.from_mp3("test.mp3")
# get raw audio data as a bytestring
raw_data = sound.raw_data
# get the frame rate
sample_rate = sound.frame_rate
# get amount of bytes contained in one sample
sample_size = sound.sample_width
# get channels
channels = sound.channels
Note that raw_data is 'on air' at this point ;). Now it's up to you how do you want to use gathered data, but this module seems to give you everything you need.