librosa

问题 I have an audio sample of about 14 seconds in 8khz Sample Rate. Im using librosa to extract some features from this audio file. y, sr = librosa.load(file_name) stft = np.abs(librosa.stft(y, n_fft=n_fft)) # file_length = 14.650022675736961 #sec # defaults # n_fft =2048 # hop_length = 512 # win_length/4 = n_fft/4 = 512 (win_length = n_fft default) #windowsTime = n_fft * Ts # (1/sr) stft.shape # (1025, 631) Specshow : librosa.display.specshow(stft, x_axis='time', y_axis='log') [![stft sr = 22050

问题 I have an audio sample of about 14 seconds in 8khz Sample Rate. Im using librosa to extract some features from this audio file. y, sr = librosa.load(file_name) stft = np.abs(librosa.stft(y, n_fft=n_fft)) # file_length = 14.650022675736961 #sec # defaults # n_fft =2048 # hop_length = 512 # win_length/4 = n_fft/4 = 512 (win_length = n_fft default) #windowsTime = n_fft * Ts # (1/sr) stft.shape # (1025, 631) Specshow : librosa.display.specshow(stft, x_axis='time', y_axis='log') [![stft sr = 22050

问题 I have about 30 sound clips that are each a preset from a synthesizer. I want to compare these sounds to find out which ones are similar, and then sort the sounds so that each sound is adjacent in a list to 2 sounds that are similar to it. Frequency is not the only thing I want to look for. I would rather 2 saw waves which are a tone apart be considered similar that a saw wave and a sine wave which are the same note. These sounds would be considered similar for example Using librosa, I have

问题 I have about 30 sound clips that are each a preset from a synthesizer. I want to compare these sounds to find out which ones are similar, and then sort the sounds so that each sound is adjacent in a list to 2 sounds that are similar to it. Frequency is not the only thing I want to look for. I would rather 2 saw waves which are a tone apart be considered similar that a saw wave and a sine wave which are the same note. These sounds would be considered similar for example Using librosa, I have

问题 When doing a STFT, and then an inverse STFT (iSTFT) on a 16 bits 44.1 khz audio file with the library Librosa : import librosa y, sr = librosa.load('test.wav', mono=False) y1 = y[0,] S = librosa.core.stft(y1) z1 = librosa.core.istft(S, dtype=y1.dtype) librosa.output.write_wav('test2.wav', z1, sr) the output is only a 22 khz audio file. Why? Where is there the sampling rate change in librosa ? 回答1: The librosa.load() function enables target sampling, wherein the audio file you import can be re

问题 When doing a STFT, and then an inverse STFT (iSTFT) on a 16 bits 44.1 khz audio file with the library Librosa : import librosa y, sr = librosa.load('test.wav', mono=False) y1 = y[0,] S = librosa.core.stft(y1) z1 = librosa.core.istft(S, dtype=y1.dtype) librosa.output.write_wav('test2.wav', z1, sr) the output is only a 22 khz audio file. Why? Where is there the sampling rate change in librosa ? 回答1: The librosa.load() function enables target sampling, wherein the audio file you import can be re

问题 I'm new to python,I'm trying get a FFT value of a uploaded wav file and return the FFT of each frame in each line of a text file (using GCP) using scipy or librosa Frame rate i require is 30fps wave file will be of 48k sample rate so my questions are how do i divide the samples for the whole wav file into samples of each frame How do add empty samples to make the length of the frame samples power of 2 (as 48000/30 = 1600 add 448 empty samples to make it 2048) how do i normalize the resulting

问题 I'm new to python,I'm trying get a FFT value of a uploaded wav file and return the FFT of each frame in each line of a text file (using GCP) using scipy or librosa Frame rate i require is 30fps wave file will be of 48k sample rate so my questions are how do i divide the samples for the whole wav file into samples of each frame How do add empty samples to make the length of the frame samples power of 2 (as 48000/30 = 1600 add 448 empty samples to make it 2048) how do i normalize the resulting

问题 When I extract MFCCs from an audio the ouput is (13, 22) . What does the number represent? Is it time frames ? I use librosa. The code is use is: mfccs = librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13, hop_length=256) mfccs print(mfccs.shape) And the ouput is (13,22) . 回答1: Yes, it is time frames and mainly depends on how many samples you provide via y and what hop_length you choose. Example Say you have 10s of audio sampled at 44.1 kHz (CD quality). When you load it with librosa, it

来源： https://stackoverflow.com/questions/60492462/mfcc-python-completely-different-result-from-librosa-vs-python-speech-features