Speech Communication - Special issue on speech processing in adverse conditions
A new approach to phoneme recognition by phoneme filter neural networks
Information Sciences: an International Journal
Phoneme recognition using wavelet based features
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Fundamental frequency estimation of voice of patients with laryngeal disorders
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Spoken language analysis, modeling and recognition-statistical and adaptive connectionist approaches
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Enhanced clustering of biomedical documents using ensemble non-negative matrix factorization
Information Sciences: an International Journal
Information Sciences: an International Journal
Multi-adjoint property-oriented and object-oriented concept lattices
Information Sciences: an International Journal
A survey of techniques for incremental learning of HMM parameters
Information Sciences: an International Journal
Privileged information for data clustering
Information Sciences: an International Journal
IEEE Transactions on Audio, Speech, and Language Processing
Convolutive Speech Bases and Their Application to Supervised Speech Separation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech
IEEE Transactions on Audio, Speech, and Language Processing
Fusion of supervised and unsupervised learning for improved classification of hyperspectral images
Information Sciences: an International Journal
Granular modelling of signals: A framework of Granular Computing
Information Sciences: an International Journal
Rough set model based on formal concept analysis
Information Sciences: an International Journal
| Hi-index | 0.07 |
This paper focuses on the development of an algorithm that can be optimized for a specific acoustic environment to improve the intelligibility of whispered speech. A new convolutive non-negative matrix factorization (NMF) algorithm is proposed to extract phoneme bases from noisy whispered speech with the noise bases from prior learning; these noise bases are obtained from training using the conventional non-negative matrix factorization. The divergence function with a sparseness constraint term is selected as the objective function in the developed algorithm to obtain multiplicative update rules of the phoneme base matrix and the corresponding weight matrix. The weights of the noise bases from prior learning are also updated in the phoneme learning stage. Listening experiments were conducted to assess the intelligibility performance of speech synthesized using the proposed algorithm. The experimental results indicate that the proposed algorithm is very effective for improving the intelligibility of whispers in various noise contexts, and it outperforms conventional algorithms.