Speech Feature
Speech features are the acoustic and linguistic characteristics extracted from speech signals, used to achieve various objectives like speech enhancement, summarization, speaker verification, and even medical diagnosis. Current research focuses on developing robust feature extraction methods using deep learning models, such as transformers and convolutional neural networks, often incorporating attention mechanisms to capture complex temporal and spectral dependencies. These advancements are improving the accuracy and efficiency of applications ranging from assistive technologies for individuals with speech impairments to enhanced security systems and improved diagnostic tools for neurological disorders.
Papers
Acoustic Room Compensation Using Local PCA-based Room Average Power Response Estimation
Wenyu Jin, Patrick McPherson, Chris Pike, Adib Mehrabi
GLD-Net: Improving Monaural Speech Enhancement by Learning Global and Local Dependency Features with GLD Block
Xinmeng Xu, Yang Wang, Jie Jia, Binbin Chen, Jianjun Hao
Robust and Complex Approach of Pathological Speech Signal Analysis
Jiri Mekyska, Eva Janousova, Pedro Gomez-Vilda, Zdenek Smekal, Irena Rektorova, Ilona Eliasova, Milena Kostalova, Martina Mrackova, Jesus B. Alonso-Hernandez, Marcos Faundez-Zanuy, Karmele López-de-Ipiña
Assessing Progress of Parkinson s Disease Using Acoustic Analysis of Phonation
Jiri Mekyska, Zoltan Galaz, Zdenek Mzourek, Zdenek Smekal, Irena Rektorova, Ilona Eliasova, Milena Kostalova, Martina Mrackova, Dagmar Berankov, Marcos Faundez-Zanuy, Karmele Lopez-de-Ipiña, Jesus B. Alonso-Hernandez