Cargando…

A Semi-Supervised Speech Deception Detection Algorithm Combining Acoustic Statistical Features and Time-Frequency Two-Dimensional Features

Human lying is influenced by cognitive neural mechanisms in the brain, and conducting research on lie detection in speech can help to reveal the cognitive mechanisms of the human brain. Inappropriate deception detection features can easily lead to dimension disaster and make the generalization abili...

Descripción completa

Detalles Bibliográficos
Autores principales:	Fu, Hongliang, Yu, Hang, Wang, Xuemei, Lu, Xiangying, Zhu, Chunhua
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216231/ https://www.ncbi.nlm.nih.gov/pubmed/37239197 http://dx.doi.org/10.3390/brainsci13050725

Ejemplares similares

Improved semi-supervised autoencoder for deception detection
por: Fu, Hongliang, et al.
Publicado: (2019)

Underwater Acoustic Target Recognition Based on Supervised Feature-Separation Algorithm
por: Ke, Xiaoquan, et al.
Publicado: (2018)

Semi-Supervised Fuzzy Clustering with Feature Discrimination
por: Li, Longlong, et al.
Publicado: (2015)

Simple strategies for semi-supervised feature selection
por: Sechidis, Konstantinos, et al.
Publicado: (2017)

Using Voice Activity Detection and Deep Neural Networks with Hybrid Speech Feature Extraction for Deceptive Speech Detection †
por: Mihalache, Serban, et al.
Publicado: (2022)

Semi-Supervised Feature Transformation for Tissue Image Classification
por: Watanabe, Kenji, et al.
Publicado: (2016)

Markers of Deception in Italian Speech
por: Spence, Katelyn, et al.
Publicado: (2012)

Feature selection and semi-supervised clustering using multiobjective optimization
por: Saha, Sriparna, et al.
Publicado: (2014)

Dynamic Encoding of Acoustic Features in Neural Responses to Continuous Speech
por: Khalighinejad, Bahar, et al.
Publicado: (2017)

Predicting couple therapy outcomes based on speech acoustic features
por: Nasir, Md, et al.
Publicado: (2017)

Selectivity to acoustic features of human speech in the auditory cortex of the mouse
por: Mohn, Jennifer L., et al.
Publicado: (2023)

Stockwell transform and semi-supervised feature selection from deep features for classification of BCI signals
por: Salimpour, Sahar, et al.
Publicado: (2022)

Statistical deception at work
por: Mauro, John
Publicado: (2013)

Design of feature selection algorithm for high-dimensional network data based on supervised discriminant projection
por: Zhang, Zongfu, et al.
Publicado: (2023)

Acoustic and Linguistic Features of Impromptu Speech and Their Association With Anxiety: Validation Study
por: Teferra, Bazen Gashaw, et al.
Publicado: (2022)

An Anti-Jamming Method against Two-Dimensional Deception Jamming by Spatial Location Feature Recognition
por: Liu, Zhidong, et al.
Publicado: (2021)

Feature selection for fMRI-based deception detection
por: Jin, Bo, et al.
Publicado: (2009)

Semi-Supervised Instance-Segmentation Model for Feature Transfer Based on Category Attention
por: Wang, Hao, et al.
Publicado: (2022)

Speech timing cues reveal deceptive speech in social deduction board games
por: Zhang, Ziyun, et al.
Publicado: (2022)

A semi-supervised approach for extracting TCM clinical terms based on feature words
por: Liu, Liangliang, et al.
Publicado: (2020)

Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM
por: Liu, Chengyin, et al.
Publicado: (2019)

Semi-supervised nuclei segmentation based on multi-edge features fusion attention network
por: Li, Huachang, et al.
Publicado: (2023)

Feature-enhanced adversarial semi-supervised semantic segmentation network for pulmonary embolism annotation
por: Cheng, Ting-Wei, et al.
Publicado: (2023)

Simple Acoustic Features Can Explain Phoneme-Based Predictions of Cortical Responses to Speech
por: Daube, Christoph, et al.
Publicado: (2019)

Speech Acoustic Features: A Comparison of Gay Men, Heterosexual Men, and Heterosexual Women
por: Suire, Alexandre, et al.
Publicado: (2020)

Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech
por: Martinc, Matej, et al.
Publicado: (2021)

Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features
por: Lee, Ming-Che, et al.
Publicado: (2022)

Acoustic speech features in social comparison: how stress impacts the way you sound
por: Kappen, Mitchel, et al.
Publicado: (2022)

Semi-Supervised Learning of Statistical Models for Natural Language Understanding
por: Zhou, Deyu, et al.
Publicado: (2014)

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition
por: Wang, Kun-Ching
Publicado: (2015)

Special feature: statistics for high-frequency data
por: Masuda, Hiroki
Publicado: (2021)

Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning
por: Zhang, Xun, et al.
Publicado: (2021)

Sintering Quality Prediction Model Based on Semi-Supervised Dynamic Time Feature Extraction Framework
por: Li, Yuxuan, et al.
Publicado: (2022)

The application of fractional Mel cepstral coefficient in deceptive speech detection
por: Pan, Xinyu, et al.
Publicado: (2015)

Pitfalls of supervised feature selection
por: Smialowski, Pawel, et al.
Publicado: (2010)

Label propagation-based semi-supervised feature selection on decoding clinical phenotypes with RNA-seq data
por: Jiang, Xue, et al.
Publicado: (2021)

Machine learning and statistical classification of birdsong link vocal acoustic features with phylogeny
por: Rivera, Moises, et al.
Publicado: (2023)

Revisiting Deception in Breonna Taylor’s Case: A Cognitive-Acoustic Approach
por: El-Zawawy, Amr M.
Publicado: (2023)

A novel semi-supervised algorithm for the taxonomic assignment of metagenomic reads
por: Le, Vinh Van, et al.
Publicado: (2016)

Semi-supervised associative classification using ant colony optimization algorithm
por: Awan, Hamid Hussain, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_baoefrqm0lccb8lapljrabse7r