Questions tagged [mfcc]

Related to the calculation, verification, usage, and requirements for Mel Frequency Cepstral Coefficients.

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Standardize MFCCs Before or After Computing Deltas?

I want to create a feature space that includes MFCCs, MFCC deltas, and MFCC delta-deltas concatenated along the time axis which I will then feed into a CNN for speech emotion recognition. After ...
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DCT vs Inverse Fourier Transform in the Final Step for Computing MFCCs [duplicate]

I've been a little confused lately about the use of these two functions in the final step of computing the MFCCs. I often see them used interchangeably, but they do the opposite thing. And my ...
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How is 76 frames calculated mfcc for 1 sec signal with 25 msec window and 10 msec overlap?

I was studying about keyword detection and while doing some reading, I read we take 1 sec audio signal. We then divide it into 25msec sub sections with and overlap of 10msec. We apply mel filter bank ...
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How to get frequencies from MFCC

So i recently learned how to graph a MFCC, but I am unable to understand what each axis means, and I know you will be like "coefficients", and "frames", but like coefficients of ...
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Is Discrete cosine transform Translational Invariant

I am using 2D Mellin-Cepstrum to extract features, If I use log-polar transform to get rotational invariance, the rotation is transformed to translation. Can I use DCT next to get translational ...
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Going from an MFCC coefficient to Hz range?

I have not worked with MFCCs before, but I am faced with the observation that the 5th MFCC of a signal is actually of interest for me in my speech research. In order to understand why that one is ...
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Combining signals in MFCC space

I'm looking at a data augmentation method for training up a neural network of speech data. Currently I have two version of augmentation. The first method works by taking an audio file and mixing in a ...
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Get Spectrogram from Filtered Power Spectrum

My objective is to get the higher resolution of spectrogram on the high-frequency area (2000 Hz - 5000 Hz) for a section of speech audio. I know that we typically apply Mel-scaled filter bank to get ...
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Logarithmic Amplitude Spectral Subtraction

I'm diving into audio processing and I'm trying to wrap my head around spectral subtraction. I learned there are different approaches do it based on power, magnitude, oversubtraction. My task is to ...
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How to compare 2 MFCC (compare them if they where created from same speaker)

There are multiple speakers. Each speaker generates multiple MFCC. If I'm getting two different MFCC, can we know if those MFCC came from 2 different speakers or same speaker ? How can we compare ...
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how to handle different durations of audio data?

I am new to signal preprocessing, I read about mel_spectrograms, MFCC's. Now I want to apply it and use the CNN model, But the data which I have for practice is having audio of different durations, ...
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Does speech volume affect frequencies?

I have created a little classifier that listens for certain keywords. Sometimes it will not react to a keyword, but if I shout the word, then the classifier will be able to pick it up. The classifier ...
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What acoustics do MFCCs correspond to?

My question is, what frequency ranges do MFCCs correspond to? My line of thinking thus far is that if your highest frequency in the signal was 8000 Hz, you could convert to Mels (= 2834 Mels), take 13 ...
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Sound feature extraction too brief in comparison with manual annotation of sound. How to combine them?

Sound characteristics (features) are taken per e.g. 20 ms, but manual annotation takes place in durations of seconds. If we want to use these characteristics along with labels, how can this be ...
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Understanding MFCC

I am not from electrical or electronic background so my knowledge will be lacking. MFCC is represented by 39 values for each window frame. 12 values are the mel filter-bank and we get 13th value by ...
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Working with a sound's magnitude instead of amplitude

I'm working on a project, where we're recording sound with a piezo-disc which looks a little something like this: Now, unless we're doing something horribly horribly wrong, I've discovered that we're ...
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Understanding MFCCs

I am doing research about emotion recognition from speech, by applying machine learning. Most papers are recommending using MFCC features. Therefore, I am currently trying to understand the underlying ...
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Amplitude of a signal. [-1, 1] vs variants and MFCC implications

I've seen two sort of audio signals, one where the y-axis takes values between -1 and +1. I'd think this means 1 means loudest? Not really sure And the second one I saw goes between $-10 000$ and $+...
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How do I interpret these mfcc graphs?

The first graph represents mfcc plot for female and the second for male. How do I interpret this graph with colors. and what is that color scale on the right? How do I differentiate gender from these ...
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Using MFCCs for acoustic machine failure prediction

MFCCs are ubiquitously extracted for speech processing tasks, but I would like to know how suitable they are for non-speech processing tasks. Intuitively, it is my understanding that MFCCs are ...
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How to train and test deep neural network using MFCC features?

I am working on Voice Disorder Detection problem. I have extracted 13 MFCC features, 13 delta and 13 delta-delta features from each audio file (2 to 4 secs). I extracted these features for each frame (...
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MATLAB: Applying Inverse Fast Fourier Transform to an array of real numbers

I'm trying to understand the difference between applying the Discrete Cosine Transform (DCT) and the Inverse Discrete Fourier Transform (IDFT) to the log Mel-filterbank energies as explained in the ...
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Understanding liftering as the final step in MFCCs features extraction

In the book here, they apply liftering, as a final step of MFCCs features extraction, to isolate the system component by multiplying the whole cepstrum by a rectangular window centred on lower ...
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Why do we use the term "cepstral" in MFCCs, and how does it related to the cepstral domain?

As I know, we can get the cepstrum by taking the Inverse Discrete Fourier Transform (IDFT) of the log of the power spectrum. And we can get the Mel-frequency cepstral coefficients (MFCCs) by taking ...
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MFCCs and mean normalization

I'm reading a blog about extracting MFCCs features for Machine Learning applications, but I didn't understand the following points about the mean normalization: To balance the spectrum and improve ...
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filterbank: understand the different responses at the center frequency of each filter

I'm computing filterbank by applying 26 triangular filters on a Mel-scale to the power spectrum of an audio frame to extract frequency bands, and I found that some references use filterbank with equal ...
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What features capture the semantics of a sentence from a gien audio?

I have been thinking lately and looking up on what could be the possible features that capture the semantics of an audio and came across MFCC: MFCC features represent phonemes (distinct units of sound)...
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Alone MFCC can identify difference between sound?

I am doing a project to identify different drum beats. There are lots of features like MFCC, Chroma Values, Spectral Bandwidth, Spectral Centroid, Zero Crossing Rate, etc. But most of the projects are ...
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Audio Activity Detection and Classification

I am starting a new project. Actually, my real intention is to learn speech recognition but for warming up I want to improve in audio signal processing. In my project, I aim to record sounds except ...
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Feature Extraction of Insect Sounds

First of all, forgive me if I sound stupid. I am still learning Audio Processing. So I am trying to make a machine learning model for detecting a specific insect through sound. Here is a sample raw ...
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239 views

Calculate the Standard Deviation of Fundamental Frequency (MFCC)

I'm implementing a gunshot detector following the article "Algorithm for Gunshot Detection Using Mel-Frequency Cepstrum Coefficients (MFCC)" (paywall). In the article, the authors uses 22 features ...
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MFCC classification model

I have audio samples which MFCCs i want to train, but there is a problem. I can't find a classification model, because the samples have different length and consequently the MFCC matrices will also ...
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what is the output of MFCCs?

I had calculated 13 MFCCs coefficients of a speech signal and i got output in the form numerical vectors please see below figure. My confusion whether it is in time domain or frequency domain. suppose ...
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Why apply filterbank in power sepstrum not log power spectrum for cepstral coefficients feature(MFCC, IMFCC, LFCC) [duplicate]

In the original method for MFCC and any other method based on cepstral coefficients The original step is like this: |FFT|^2 -> Filterbank -> Log -> DCT but why not like that: |FFT|^2 -> Log -> ...
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How to overcome different MFCC coefficients distributions from different speech datasets?

I am using MFCC values as features for a machine learning model of speech, detecting age from a voice recording of a person. I work with voice datasets I found on the web: common-voice and vctk. ...
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why the MFCC is gender indenpend and used for isolated word recognition

I think female and male have total different MFCC feature for same word such as "one", but why the MFCC could be used for isolated word recognition which use the same HMM model for the same word ...
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What does mean when we say mel scale reflects how humans hear musical tone [duplicate]

According to the standard mel frequency conversion formula, the mel frequency corresponding to 10000 Hz is 3073.22. Does it mean human ears perceive 10000 Hz frequency of any sound as 3073.22 Hz?
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How can I modify a sound signal based on it's MFCC

I'm working on an NN algorithm with which I want to filter noise from sound signals. I have some clean speech sound samples and noise samples, by combining them I get the signal that I want to filter....
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1 vote
1 answer
711 views

audio signal reconstruction from MFCC

Transforming an audio signal to Mel Frequency Cepstral Coefficients is broadly used in tasks involving learning on audio. I was wondering, is this transform invertible with some good approximability ...
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Fast Fourier Transform using numpy

I am a computer science student and didn't really have signal processing as a subject. Maybe I should be clear on the concepts of sampling rate and frequency of the signal but I am a little confused. ...
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1 answer
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Two voice pronunciation comparison similarity MFCC + DTW

Calculate each MFCC to compare wave file A and wave file B, and then use FastDTW to measure the distance after two sets of MFCCs. We compared the four wave files and obtained the Euclidean distance ...
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How does a telephone change your voice? [closed]

Is it due to vocal length normalization during MFCC? Please be kind enough to explain.
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2 votes
2 answers
2k views

MFCC window size at different sampling rates

The general recommendation for window size when calculating MFCC seems to be 20-40 msec. This is most often recommended in a context of 16000 samples per second, so leading to a window containing 320-...
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Given MFCC values for some wav’s, how can I easily tell if all speakers are the same?

Context: for a research project I have at regular times a batch of wav files with recordings of voice. The hypothesis is that all speakers in a batch are the same, but there might be 1 or a few “...
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issue with the MFCC and GMM for audio recognition

i am working on a project related to audio events recognition in real time like a door bell, baby crying, footstep, I have 9 categories of sound events so the first step i did was getting many wav ...
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issue in the mfcc function in java and matlab,not the same

I am working on a project for recognizing and identifying the sounds in real time(like baby crying, birds, door knocking...)by java, so I made a model by using audio files for 9 categories of sound by ...
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Why MFCC have varying length dimensions?

I have recently started to use MFCC as a feature for a project. However, I am unable to understand why MFCC have varying 2nd dimension size even when I chose the number of coefficients to be 40.
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Speech Processing applications: stereo data for features

I am working on speech databases that have a stereo format. I want to extract spectral information (Mel-filterbanks, MFCC, LPCC) and also some other prosody features like the fundamental Frequency F0. ...
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2 answers
105 views

Is there such thing as harmony independent timbre characteristic of a sound?

I was wondering if any of you know about any technique to extract a harmony (e.g. harmony in a shape of a chromagram) independent timbre characteristic of a sound frame. What I'm after is a version ...
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Machine Learning - any suggestions to solve Python rounding errors?

I am working with Python to isolate voiced segments from music using the Jamendo corpus for singing detection. Training a model, I break my audio into frames, and have a label (0,1) for each frame. ...
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