다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기
Applied acoustics, v.156, 2019년, pp.351 - 358
Ertam, Fatih
AI-Helper
Abstract It is not difficult to estimate the gender of the human from other people's audio files. In general, people can easily identify the gender of the owner of a conversation with the experience they have acquired. However, it is not easy to predict whether a person is a man or a woman by compu...
10.21437/Interspeech.2010-747 Li M, Jung C-S, Han KJ. 2010. Combining Five Acoustic Level Modeling Methods for Automatic Speaker Age and Gender Recognition. In: 11Th Annu. Conf. Int. Speech Commun. Assoc. 2010 (Interspeech 2010), Vols 3 4, 2010, p. 2830+.
Digit Signal Process A Rev J Chen 89 104 2019 10.1016/j.dsp.2019.03.008 A bilevel framework for joint optimization of session compensation and classification for speaker identification
Knowledge-Based Syst Qawaqneh 2017 10.1016/j.knosys.2016.10.008 Deep neural network framework and transformed MFCCs for speaker’s age and gender classification
Corpus Black 2030 2010 Automatic Classification of Married Couples’ Behavior using Audio Features
Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) Nguyen 2010 Automatic speech-based classification of gender, age and accent
Mach Learn Knowl Extr Livieris 1 492 2019 10.3390/make1010030 Gender Recognition by Voice using an Improved Self-Labeled Algorithm
10.1109/ICASSP.2007.367263 Metze F, Ajmera J, Englert R, Bub U, Burkhardt F, Stegmann J, et al. 2007. Comparison of four approaches to age and gender recognition for telephone applications. In: ICASSP, IEEE Int. Conf. Acoust. Speech Signal Process. - Proc., vol. 4, 2007. doi:10.1109/ICASSP.2007.367263.
10.1109/IJCNN.1992.226966 Konig Y, Morgan N. 2003. GDNN: a gender-dependent neural network for continuous speech recognition, pp. 332-7. doi:10.1109/ijcnn.1992.226966.
Speaker and gender normalization for continuous-density hidden Markov models Acero 342 2002 Xuedong Huang
Phone-context specific gender-dependent acoustic-models for continuous speech recognition Neti 192 2002
DEStech Trans Comput Sci Eng Ramadhan 2017 10.12783/dtcse/cece2017/14611 Parameter Tuning in Random Forest Based on Grid Search Method for Gender Classification Based on Voice Frequency
10.1109/ICME.2003.1221721 Harb H, Chen L. 2003. Gender identification using a general audio classifier. In: Proc. - IEEE Int. Conf. Multimed. Expo, vol. 2, 2003. pp. II733-6. doi:10.1109/ICME.2003.1221721.
J Voice Huestegge 2018 10.1016/j.jvoice.2018.09.020 Crossing Gender Borders: Bidirectional Dynamic Interaction Between Face-Based and Voice-Based Gender Categorization
J Voice Zourmand 27 201 2013 10.1016/j.jvoice.2012.12.006 Gender classification in children based on speech characteristics: using fundamental and formant frequencies of Malay vowels
Appl Acoust Barkana 98 52 2015 10.1016/j.apacoust.2015.04.013 A new pitch-range based feature set for a speaker’s age and gender classification
Int J Image, Graph Signal Process Pahwa 8 17 2015 10.5815/ijigsp.2015.09.03 Speech Feature Extraction for Gender Recognition
Voice Gender Recognition Using Deep Learning Buyukyilmaz 2017
10.1109/ICABCD.2018.8465466 Zvarevashe K, Olugbara OO. 2018. Gender Voice Recognition Using Random Forest Recursive Feature Elimination with Gradient Boosting Machines. In: 2018 Int. Conf. Adv. Big Data, Comput. Data Commun. Syst. icABCD 2018, 2018. doi:10.1109/ICABCD.2018.8465466.
Concurr Comput Ay Karakuş 30 2018 10.1002/cpe.4783 Evaluating deep learning models for sentiment classification
Neural Comput Hochreiter 9 1735 1997 10.1162/neco.1997.9.8.1735 Long Short-Term Memory
Renew Energy Lei 133 422 2019 10.1016/j.renene.2018.10.031 Fault diagnosis of wind turbine based on Long Short-term memory networks
J Comput Sci Kong 26 78 2018 10.1016/j.jocs.2018.03.010 Construction of intelligent traffic information recommendation system based on long short-term memory
PLoS ONE Bao 12 2017 10.1371/journal.pone.0180944 A deep learning framework for financial time series using stacked autoencoders and long-short term memory
Voice Dataset n.d. https://www.kaggle.com/primaryobjects/voicegender.
Proc Int Conf Inven Commun Comput Technol ICICCT 2018 Pondhu 2018 Performance Analysis of Machine Learning Algorithms for Gender Classification
Pattern Recognit Zhang 35 701 2002 10.1016/S0031-3203(01)00046-2 Feature selection using tabu search method
Mach Learn Proc Kira 2014 249 1992 A Practical Approach to Feature Selection
Behav Brain Res Jin 356 400 2019 10.1016/j.bbr.2018.09.003 A ReliefF-SVM-based method for marking dopamine-based disease characteristics: a study on SWEDD and Parkinson’s disease
Expert Syst Appl Aviad 38 8220 2011 10.1016/j.eswa.2011.01.001 Classification by clustering decision tree-like classifier based on adjusted clusters
Chemom Intell Lab Syst Siqueira 162 123 2017 10.1016/j.chemolab.2017.01.021 Araújo Júnior RF, de Araújo AA, Morais CLM, Lima KMG. LDA vs. QDA for FT-MIR prostate cancer tissue classification
Mach Learn Schein 68 235 2007 10.1007/s10994-007-5019-5 Active learning for logistic regression: An evaluation
IEEE Trans Neural Networks Learn Syst Zhang 29 1774 2018 10.1109/TNNLS.2017.2673241 Efficient kNN classification with different numbers of nearest neighbors
Artif Intell Med Koopman 89 1 2018 10.1016/j.artmed.2018.04.011 Extracting cancer mortality statistics from death certificates: a hybrid machine learning and rule-based approach for common and rare cancers
Expert Syst Appl Raghu 113 18 2018 10.1016/j.eswa.2018.06.031 Classification of focal and non-focal EEG signals using neighborhood component analysis and machine learning algorithms
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Copyright KISTI. All Rights Reserved.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.