MFCC & Speech Pattern Matching : Inspired by Siamese Networks!
In this video, we explore how Mel-Frequency Cepstral Coefficients #mfcc are used to process speech signals by capturing essential frequency features. MFCCs provide a compact representation of audio, making them a powerful tool for speech pattern matching. We demonstrate how to calculate the distance between MFCC feature vectors to compare different speech signals, an approach inspired by #Siamese Networks, which are widely used in #facerecognition recognition. This method allows #ai systems to analyze and distinguish #speech #patterns efficiently, opening doors to applications like speaker verification, voice #biometrics, and sound classification. Watch now to understand the intersection of speech processing and deep learning!
Видео MFCC & Speech Pattern Matching : Inspired by Siamese Networks! канала Learn AI with Anand
Видео MFCC & Speech Pattern Matching : Inspired by Siamese Networks! канала Learn AI with Anand
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17 марта 2025 г. 20:21:45
01:24:48
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