Комментарии:
If signal is sampled at sr = 22050 Hz and while calculating MFCC it is mentioned as sr = 44100 Hz. Theoretically what will happen?
Ответитьhow can we extract tqwt features from audio??
ОтветитьWhat's the Debussy piece you played?? First time hearing it
ОтветитьHow do we normalize the mfcc using cepstral mean and variance?
ОтветитьThank you so much, Valerio!! Super helpful content and super clear steps to help me get my MFCCs.
Ответитьthanks alot ,, but how i can get mfcc feature as a matrix not a plot figure
Ответитьare we getting MFCC from STFT or FFT ?
Ответитьonly three videos left and I made it throught the entire course/playlist. At this point I want to thank you for all that. This was exactly what I was searching for and now I am ready to start my Bachelor thesis about "ai in music" what is definitely the niché in which I want to get really really good
ОтветитьHi Thanks for the informative video. Based on the concatenated output of mfcc and delta, can you guide which value to be considered to find the uniqueness in a speakers voice. Or on the top of this model, should we build some more dataset and train the model to identify the uniqueness in a voice for biometric?
ОтветитьThank You, MAN
ОтветитьHi, how to compare with 2 audio's? and result will show precentage.
Ответитьhow to extract spatial features of an audio from the mfcc values by using inception resnet v2 and how extract temporal features using lstm model
Ответитьi want to ask is there any difference between using only librosa.feature.mfcc and extracting manually the mfcc by changing the audio to FT,FTT first? thank you
Ответитьhow to extract mfcc for group of files in folders and save plot
ОтветитьThanks a lot sir very nice video
Ответитьloved this videos, thank you !
ОтветитьMFCC or mel spectrogram? which one is preferable and where why? unable to find answer
ОтветитьDear author, thank you very much, the content is very usefull!!! Could you please explain, why you don't set the number of mel-filters when you apply < librosa.feature.mfcc(...) > ?
Ответитьthank you it does help a lot :)
Ответитьthis helped me so much. i tried every other ways but only this worked as it was shown. Thank you.
Ответитьwhy i have error at part idp.Audio(audio_file) ? the audio cannot display
ОтветитьThank you sir for these videos! Can you please make videos on CQCC feature extraction?
ОтветитьThank you for the informative video. But I have some questions. Do I have to perform pre-emphasis or I can just use the MFCCs directly?
ОтветитьNice Video. How do we interpret the MFCCs?
ОтветитьHas anyone implemented mfcc and hmm for speech emotion recognition using Matlab?
Ответитьhow I extract MFCC from multi-audio at once ?? can I??
ОтветитьI'm trying to figure out what is the significance of a positive versus negative MFCC intensity value, especially over time. If the value for MFCC 8, for example, was to consistently remain negative, but become more positive (from -0.05 to -0.03) what is that indicating?
ОтветитьFirst of all, Thank you very much Mr. Valerio Velardo. Your all videos are very helpful for learners. I have one please Could you explain FFT and MFCCs in numpy? Thanks a lot in advance.
ОтветитьWhat's the point of concatenating the MFCC's with the derivative
ОтветитьThank you for your videos! So clear and helpful
Ответитьcan we calculate timbre from mfcc
ОтветитьI did this with an audio file of Dysarthric person and even got the output. Now how should I explain the visualisation to my project guide.
Ответитьplease tell me, I found an error here...in 4th cell..
# load audio files with librosa
signal, sr = librosa.load(audio_file)
attribute error...
Is concatenating them better than putting each of them into a different channel? Also, how would you normalize each of these? Do you do it the MFCC / delta / delta2 individually before concatenating? Do you use minmax normalization or standardization? Do you apply this to each "image" individually or do you use the entire training dataset's statistics? Thanks!
ОтветитьHi, very useful video! To do some simple sound classification, can I just do it with the MFCC's or would you recommend to use the derivatives or concatination?
ОтветитьAnother great video. This is amazing! Just one question if you don't mind, Valerio: Does the librosa.feature.mfcc method consider frame sizes of 512 by default? (30/1292*sr=512)
ОтветитьThank you for this videos! Really helpful
ОтветитьThis is the what i was looking for! Thank you so much!
ОтветитьYour video is great!
excuse me ! whats the n_mfcc mean ?
Can we use MFCCs for music generation?
Ответитьawesome way to explain.
ОтветитьI had absolutely no idea what I was doing when it came to MFCCs for my electronic stethoscope project, this is exactly the content I needed! Really helpful.
ОтветитьThank you, Valerio. Great content
ОтветитьThanks Valerio for such a great content
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