Introduction to algorithms
Fundamentals of speech recognition
Fundamentals of speech recognition
An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Fast Algorithms for Digital Signal Processing
Fast Algorithms for Digital Signal Processing
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
A hybrid approach of NN and HMM for facial emotion classification
Pattern Recognition Letters
Speech enhancement by map spectral amplitude estimation using a super-Gaussian speech model
EURASIP Journal on Applied Signal Processing
Discrete-time speech signal processing: principles and practice
Discrete-time speech signal processing: principles and practice
Inventory based speech enhancement for speaker dedicated speech communication systems
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
HMM-Based Gain Modeling for Enhancement of Speech in Noise
IEEE Transactions on Audio, Speech, and Language Processing
Codebook driven short-term predictor parameter estimation for speech enhancement
IEEE Transactions on Audio, Speech, and Language Processing
Noisy Speech Enhancement Using Harmonic-Noise Model and Codebook-Based Post-Processing
IEEE Transactions on Audio, Speech, and Language Processing
Evaluation of Objective Quality Measures for Speech Enhancement
IEEE Transactions on Audio, Speech, and Language Processing
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
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We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted signal we are resynthesizing a new "clean" signal based on its likely characteristics. These characteristics are estimated from the distorted signal. A successful implementation of the proposed method is presented. Experiments were performed in a scenario with roughly one hour of clean speech training data. Our results show that the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments. Potential applications for the proposed method include jet cockpit communication systems and offline methods for the restoration of audio recordings.