Professional MATLAB source code with comprehensive documentation and examples
Speech Enhancement Results Evaluation Framework featuring four speech quality assessment methods: Signal-to-Noise Ratio (SNR), Segmental SNR (segSNR), Log Spectral Distance (LSD), and Perceptual Evaluation of Speech Quality (PESQ). Includes MATLAB im
In frequency-domain blind source separation (BSS) for speech signals using independent component analysis (ICA), a practical parametric Pearson distribution system is employed to model the statistical distribution of frequency-domain source component
MATLAB program for audio signal endpoint detection using short-term average energy and short-term average zero-crossing rate to determine speech boundaries, including SNR calculation module for audio quality assessment.
This MATLAB toolbox for speech recognition and speech enhancement serves as an excellent reference implementation, featuring key algorithms like spectral subtraction, Wiener filtering, and deep learning-based enhancement techniques with practical cod
This speech synthesis algorithm implements a time-domain Pitch Synchronous Overlap-Add (PSOLA) approach, performing prosodic feature extraction, modification, and waveform synthesis including short-term energy analysis and short-term zero-crossing ra
The KSVD algorithm employs training-based methods to construct sparse overcomplete dictionaries. Implementation requires ompbox9 installation. This sparse dictionary construction approach can be applied to signal processing domains including speech a
An efficient, ready-to-run HMM-GMM code implementation complete with speech datasets. This beginner-friendly example contains no technical barriers and provides clear insights into hidden Markov models combined with Gaussian mixture models for speech
The PESQ (Perceptual Evaluation of Speech Quality) metric evaluates speech quality using a MATLAB-compatible function syntax: [pesq_mos] = pesq('cleanfile.wav', 'enhanced.wav'). This function compares reference and processed audio files to generate a
This audio watermark embedding demonstration interface features high embedding capacity, providing a valuable reference implementation for your applications.
Extraction of speech signal features, including methods for obtaining Mel Frequency Cepstral Coefficients (MFCC), principles of linear prediction for speech signals, and derivation of LPC features with code implementation insights
Approximate K-SVD algorithm for dictionary update in dictionary-learning-based speech enhancement, incorporating OMP algorithm for sparse coding to compute coefficient matrices with code-level implementation insights
A DHMM program designed for speech recognition applications, providing significant guidance on DHMM implementation with practical code examples
Independent Component Analysis (ICA) has evolved over the past two decades as a blind source separation method. This statistical technique aims to recover statistically independent source signals from mixed signals collected by sensors, with applicat
Neural network speech recognition technology and its implementation using deep learning architectures for converting human speech into text.
mp3read and mp3write are designed as complete syntax-compatible replacements for MATLAB's wavread and wavwrite functions specifically for handling MPEG audio MP3 files. Key implementation features include: - Complete replication of wavread/wavwrite s
Objective evaluation methods for synthetic speech quality, encompassing metrics such as Signal-to-Noise Ratio (SNR), Cepstral Distance, and Mean Value, implemented using MATLAB programs with detailed algorithmic explanations.
This set of programs provides a wavelet transform-based speech denoising routine, where each program's specific functionality can be found in the source code.
DTMF (Dual-Tone Multi-Frequency) is an encoding technique that uses specific pairs of audio frequency tones to represent digit signals, where different frequency combinations correspond to different numbers or functions. This system utilizes 8 distin
Filter Design for Speech Signal Processing Using MATLAB with Implementation Methods
Comprehensive speech recognition preprocessing workflow including voice preprocessing and MFCC feature parameter extraction with code implementation details