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 *

185 related articles for article (PubMed ID: 35853398)

  • 1. Deep learning applications in telerehabilitation speech therapy scenarios.
    Mulfari D; La Placa D; Rovito C; Celesti A; Villari M
    Comput Biol Med; 2022 Sep; 148():105864. PubMed ID: 35853398
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Dysarthric Speech Transformer: A Sequence-to-Sequence Dysarthric Speech Recognition System.
    Shahamiri SR; Lal V; Shah D
    IEEE Trans Neural Syst Rehabil Eng; 2023; 31():3407-3416. PubMed ID: 37603475
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Optimising Speaker-Dependent Feature Extraction Parameters to Improve Automatic Speech Recognition Performance for People with Dysarthria.
    Marini M; Vanello N; Fanucci L
    Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640780
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Speech Vision: An End-to-End Deep Learning-Based Dysarthric Automatic Speech Recognition System.
    Shahamiri SR
    IEEE Trans Neural Syst Rehabil Eng; 2021; 29():852-861. PubMed ID: 33929963
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The use of speech recognition technology by people living with amyotrophic lateral sclerosis: a scoping review.
    Cave R; Bloch S
    Disabil Rehabil Assist Technol; 2023 Oct; 18(7):1043-1055. PubMed ID: 34511007
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech.
    Agarwalla S; Sarma KK
    Neural Netw; 2016 Jun; 78():97-111. PubMed ID: 26783204
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An Internet-based telerehabilitation system for the assessment of motor speech disorders: a pilot study.
    Hill AJ; Theodoros DG; Russell TG; Cahill LM; Ward EC; Clark KM
    Am J Speech Lang Pathol; 2006 Feb; 15(1):45-56. PubMed ID: 16533092
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A speech-controlled environmental control system for people with severe dysarthria.
    Hawley MS; Enderby P; Green P; Cunningham S; Brownsell S; Carmichael J; Parker M; Hatzis A; O'Neill P; Palmer R
    Med Eng Phys; 2007 Jun; 29(5):586-93. PubMed ID: 17049905
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automatic speech recognition (ASR) and its use as a tool for assessment or therapy of voice, speech, and language disorders.
    Kitzing P; Maier A; Ahlander VL
    Logoped Phoniatr Vocol; 2009; 34(2):91-6. PubMed ID: 19173117
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of an Automatic Speech Recognition Platform for Dysarthric Speech.
    Calvo I; Tropea P; Viganò M; Scialla M; Cavalcante AB; Grajzer M; Gilardone M; Corbo M
    Folia Phoniatr Logop; 2021; 73(5):432-441. PubMed ID: 33190131
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The relationship between perceptual disturbances in dysarthric speech and automatic speech recognition performance.
    Tu M; Wisler A; Berisha V; Liss JM
    J Acoust Soc Am; 2016 Nov; 140(5):EL416. PubMed ID: 27908075
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A multi-views multi-learners approach towards dysarthric speech recognition using multi-nets artificial neural networks.
    Shahamiri SR; Salim SS
    IEEE Trans Neural Syst Rehabil Eng; 2014 Sep; 22(5):1053-63. PubMed ID: 24760940
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Characterizing Dysarthria Diversity for Automatic Speech Recognition: A Tutorial from the Clinical Perspective.
    Rowe HP; Gutz SE; Maffei MF; Tomanek K; Green JR
    Front Comput Sci; 2022 Apr; 4():. PubMed ID: 37860708
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automated Dysarthria Severity Classification: A Study on Acoustic Features and Deep Learning Techniques.
    Joshy AA; Rajan R
    IEEE Trans Neural Syst Rehabil Eng; 2022; 30():1147-1157. PubMed ID: 35452390
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic boost articulation therapy in adults with dysarthria: Acceptability, usability and user interaction.
    Mendoza Ramos V; Vasquez-Correa JC; Cremers R; Van Den Steen L; Nöth E; De Bodt M; Van Nuffelen G
    Int J Lang Commun Disord; 2021 Sep; 56(5):892-906. PubMed ID: 34227721
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Interaction between people with dysarthria and speech recognition systems: A review.
    Jaddoh A; Loizides F; Rana O
    Assist Technol; 2023 Jul; 35(4):330-338. PubMed ID: 35435810
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Vocal tract representation in the recognition of cerebral palsied speech.
    Rudzicz F; Hirst G; van Lieshout P
    J Speech Lang Hear Res; 2012 Aug; 55(4):1190-207. PubMed ID: 22271873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A proof-of-concept study for automatic speech recognition to transcribe AAC speakers' speech from high-technology AAC systems.
    Chen SK; Saeli C; Hu G
    Assist Technol; 2024 Jul; 36(4):319-326. PubMed ID: 37748185
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Improving Dysarthric Speech Segmentation With Emulated and Synthetic Augmentation.
    Naeini SA; Simmatis L; Jafari D; Yunusova Y; Taati B
    IEEE J Transl Eng Health Med; 2024; 12():382-389. PubMed ID: 38606392
    [TBL] [Abstract][Full Text] [Related]  

  • 20. On the development of speech resources for the Mixtec language.
    Caballero-Morales SO
    ScientificWorldJournal; 2013; 2013():170649. PubMed ID: 23710134
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.