Spectrogram Plotting for Speech Signals
MATLAB Implementation for Speech Signal Spectrogram Visualization with Adjustable Parameters
Professional MATLAB source code with comprehensive documentation and examples
MATLAB Implementation for Speech Signal Spectrogram Visualization with Adjustable Parameters
A comprehensive guide to implementing speech recognition systems using Hidden Markov Models, covering data preprocessing, model training, feature matching, decoding, and optimization techniques with code-related explanations.
A robust pitch period feature extraction program suitable for speech recognition applications, implementing advanced signal processing algorithms for accurate fundamental frequency detection.
This MATLAB program performs audio signal noise reduction and can be customized with code modifications to implement additional functionality, featuring various digital signal processing algorithms.
MFCC, or Mel-Frequency Cepstral Coefficients, represent one of the fundamental features in speech signal processing that effectively models human auditory perception. The computational pipeline involves preprocessing, windowing, Fourier transformatio
Pitch period extraction algorithm in speech signal processing using linear prediction methodology, implemented with MATLAB including code implementation details and key function explanations.
Speech signals often exhibit reverberation effects during enhancement processes. To eliminate background reverberation, speakers frequently need to adjust their head orientation, causing continuous variations in impulse responses. We combine blind de
Speech signal denoising implementation in MATLAB environment, performing wavelet transform on noisy speech signals, applying threshold-based denoising principles, and reconstructing enhanced speech signals through inverse transformation with detailed
Audio watermarking source code that embeds pseudo-random sequences into audio signals, implementing digital signal processing techniques for information hiding through XOR operations and pseudo-random sequence generation.
The system enables the generation of echo-added audio files from sound signals, facilitates echo cancellation to recover the original signal, and additionally estimates the distance of reflective objects based on acoustic characteristics.
This project implements the RLS (Recursive Least Squares) algorithm using MATLAB for adaptive interference cancellation. The implementation includes performance validation with provided signal examples: ① mixed speech-noise signal (signalnosie.wav) a
Spectral Variance for Voice Activity Detection: Practical MATLAB implementation featuring signal processing algorithms, FFT-based spectral analysis, and threshold-based endpoint detection methods.
Speech Recognition is a technology that enables machines to convert speech signals into corresponding text or commands through identification and comprehension processes. This project conducts preliminary exploration and research on isolated word rec
Source code implementation of the latest international speaker recognition algorithm with built-in voice training dataset
Source code for a MATLAB-based audio signal spectrum analyzer with detailed implementation
Classical noise estimation for speech enhancement with practical algorithm considerations
MATLAB implementation of spectral subtraction noise reduction technique, including source code, comparison of original and noise-reduced speech signals, and experimental results visualization.
MATLAB-based implementation of pitch period detection in speech signals using the Average Magnitude Difference Function (AMDF) approach
A MATLAB program for windowing and frame segmentation of speech signals with capability for independent window application on any individual frame.
Two algorithms for subspace speech enhancement, both based on Loizou's research papers, with implementation considerations for spectral subtraction and signal subspace approaches.