These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

139 related articles for article (PubMed ID: 22255973)

  • 1. Telephone-quality pathological speech classification using empirical mode decomposition.
    Kaleem MF; Ghoraani B; Guergachi A; Krishnan S
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():7095-8. PubMed ID: 22255973
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Pathological speech signal analysis and classification using empirical mode decomposition.
    Kaleem M; Ghoraani B; Guergachi A; Krishnan S
    Med Biol Eng Comput; 2013 Jul; 51(7):811-21. PubMed ID: 23460198
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model.
    Ali Z; Elamvazuthi I; Alsulaiman M; Muhammad G
    J Voice; 2016 Nov; 30(6):757.e7-757.e19. PubMed ID: 26522263
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Telephony-based voice pathology assessment using automated speech analysis.
    Moran RJ; Reilly RB; de Chazal P; Lacy PD
    IEEE Trans Biomed Eng; 2006 Mar; 53(3):468-77. PubMed ID: 16532773
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Using modulation spectra for voice pathology detection and classification.
    Markaki M; Stylianou Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():2514-7. PubMed ID: 19964970
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Speech enhancement using empirical mode decomposition and the Teager-Kaiser energy operator.
    Khaldi K; Boudraa AO; Komaty A
    J Acoust Soc Am; 2014 Jan; 135(1):451-9. PubMed ID: 24437785
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Discrimination of pathological voices using a time-frequency approach.
    Umapathy K; Krishnan S; Parsa V; Jamieson DG
    IEEE Trans Biomed Eng; 2005 Mar; 52(3):421-30. PubMed ID: 15759572
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Optimal selection of wavelet-packet-based features using genetic algorithm in pathological assessment of patients' speech signal with unilateral vocal fold paralysis.
    Behroozmand R; Almasganj F
    Comput Biol Med; 2007 Apr; 37(4):474-85. PubMed ID: 17034780
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Investigation of Voice Pathology Detection and Classification on Different Frequency Regions Using Correlation Functions.
    Al-Nasheri A; Muhammad G; Alsulaiman M; Ali Z
    J Voice; 2017 Jan; 31(1):3-15. PubMed ID: 26992554
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.
    Cordeiro H; Fonseca J; Guimarães I; Meneses C
    J Voice; 2017 May; 31(3):384.e9-384.e14. PubMed ID: 27743845
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Statistical voice activity detection in kernel space.
    Kim DK; Chang JH
    J Acoust Soc Am; 2012 Oct; 132(4):EL303-9. PubMed ID: 23039569
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The optimal ratio time-frequency mask for speech separation in terms of the signal-to-noise ratio.
    Liang S; Liu W; Jiang W; Xue W
    J Acoust Soc Am; 2013 Nov; 134(5):EL452-8. PubMed ID: 24181990
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Analysis and Classification of Voice Pathologies Using Glottal Signal Parameters.
    Forero M LA; Kohler M; Vellasco MM; Cataldo E
    J Voice; 2016 Sep; 30(5):549-56. PubMed ID: 26474715
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Comparison of Cepstral Peak Prominence Measures From Two Acoustic Analysis Programs.
    Watts CR; Awan SN; Maryn Y
    J Voice; 2017 May; 31(3):387.e1-387.e10. PubMed ID: 27751661
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fuzzy logic based classification and assessment of pathological voice signals.
    Aghazadeh BS; Heris HK
    Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():328-31. PubMed ID: 19964477
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multidirectional regression (MDR)-based features for automatic voice disorder detection.
    Muhammad G; Mesallam TA; Malki KH; Farahat M; Mahmood A; Alsulaiman M
    J Voice; 2012 Nov; 26(6):817.e19-27. PubMed ID: 23177748
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research.
    Lebacq J; Schoentgen J; Cantarella G; Bruss FT; Manfredi C; DeJonckere P
    J Voice; 2017 Sep; 31(5):550-556. PubMed ID: 28320627
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automatic intelligibility assessment of speakers after laryngeal cancer by means of acoustic modeling.
    Bocklet T; Riedhammer K; Nöth E; Eysholdt U; Haderlein T
    J Voice; 2012 May; 26(3):390-7. PubMed ID: 21820272
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?
    Ali Z; Alsulaiman M; Muhammad G; Elamvazuthi I; Al-Nasheri A; Mesallam TA; Farahat M; Malki KH
    J Voice; 2017 May; 31(3):386.e1-386.e8. PubMed ID: 27745756
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A new approach to discriminative HMM training for pathological voice classification.
    Sarria-Paja M; Castellanos-Dominguez G; Delgado-Trejos E
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():4674-7. PubMed ID: 21096005
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.