Pre-Processing audio data for whale sound classification using CNN
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Previous researchers have used techniques like Denoising using Spectral Subtraction method and calculating Short Time Fourier Transform (STFT) by dividing the audio data into fixed size chunks and then calculating the frame spectrogram for each of these chunks.
The image below shows how the author has pre-processed his data by manually extracting the frame and calculating it's spectrogram after applying the above-mentioned methods.
What pre-processing techniques exist for such kind of audio data where you need to use the spectrogram images for developing a CNN model, given that all audio files will be of varying length and bit-rates?
machine-learning python cnn data-cleaning preprocessing
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$begingroup$
Previous researchers have used techniques like Denoising using Spectral Subtraction method and calculating Short Time Fourier Transform (STFT) by dividing the audio data into fixed size chunks and then calculating the frame spectrogram for each of these chunks.
The image below shows how the author has pre-processed his data by manually extracting the frame and calculating it's spectrogram after applying the above-mentioned methods.
What pre-processing techniques exist for such kind of audio data where you need to use the spectrogram images for developing a CNN model, given that all audio files will be of varying length and bit-rates?
machine-learning python cnn data-cleaning preprocessing
New contributor
$endgroup$
add a comment |
$begingroup$
Previous researchers have used techniques like Denoising using Spectral Subtraction method and calculating Short Time Fourier Transform (STFT) by dividing the audio data into fixed size chunks and then calculating the frame spectrogram for each of these chunks.
The image below shows how the author has pre-processed his data by manually extracting the frame and calculating it's spectrogram after applying the above-mentioned methods.
What pre-processing techniques exist for such kind of audio data where you need to use the spectrogram images for developing a CNN model, given that all audio files will be of varying length and bit-rates?
machine-learning python cnn data-cleaning preprocessing
New contributor
$endgroup$
Previous researchers have used techniques like Denoising using Spectral Subtraction method and calculating Short Time Fourier Transform (STFT) by dividing the audio data into fixed size chunks and then calculating the frame spectrogram for each of these chunks.
The image below shows how the author has pre-processed his data by manually extracting the frame and calculating it's spectrogram after applying the above-mentioned methods.
What pre-processing techniques exist for such kind of audio data where you need to use the spectrogram images for developing a CNN model, given that all audio files will be of varying length and bit-rates?
machine-learning python cnn data-cleaning preprocessing
machine-learning python cnn data-cleaning preprocessing
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asked 1 hour ago
Abhishek SinghAbhishek Singh
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Abhishek Singh is a new contributor. Be nice, and check out our Code of Conduct.
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