Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Gender recognition from speech. Part I: Coarse analysis.

K Wu1, D G Childers

  • 1Entropic Speech, Inc., Cupertino, California 95014.

The Journal of the Acoustical Society of America
|October 1, 1991
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Study on the effects of noise on hypertension and hyperglycemia among occupational workers].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases·2020
Same author

Reduced E-cadherin expression as a prognostic factor in non-muscle-invasive bladder cancer: A systematic review and meta-analysis.

Progres en urologie : journal de l'Association francaise d'urologie et de la Societe francaise d'urologie·2020
Same author

Immediate early response protein 2 promotes the migration and invasion of hepatocellular carcinoma cells via regulating the activity of Rho GTPases.

Neoplasma·2020
Same author

Measures of body fatness and height in early and mid-to-late adulthood and prostate cancer: risk and mortality in The Pooling Project of Prospective Studies of Diet and Cancer.

Annals of oncology : official journal of the European Society for Medical Oncology·2020
Same author

Role of 3D Pseudocontinuous Arterial Spin-Labeling Perfusion in the Diagnosis and Follow-Up in Patients with Herpes Simplex Encephalitis.

AJNR. American journal of neuroradiology·2019
Same author

Long noncoding RNA NEAT1 promotes the growth of gastric cancer cells by regulating miR-497-5p/PIK3R1 axis.

European review for medical and pharmacological sciences·2019

Digital speech processing effectively recognizes gender using acoustic coefficients. Gender information in speech is largely independent of time, phonemes, and speaker identity, enabling high classification accuracy.

Area of Science:

  • Speech processing
  • Pattern recognition
  • Acoustic analysis

Background:

  • Automatic gender recognition from speech is an active research area.
  • Acoustic features of speech segments are crucial for distinguishing speaker characteristics.
  • Previous studies have explored various acoustic parameters for speaker identification.

Purpose of the Study:

  • To investigate the effectiveness of digital speech processing and pattern recognition for automatic gender recognition.
  • To evaluate different acoustic coefficients, distance measures, and recognition schemes.
  • To determine the invariance of gender-specific speech information.

Main Methods:

  • Utilized coarse acoustic coefficients (autocorrelation, linear prediction, cepstrum, reflection) for template formation.

Related Experiment Videos

  • Assessed vowels, voiced fricatives, and unvoiced fricatives.
  • Compared various distance measures (e.g., Euclidean), filter orders, and recognition schemes.

    • Main Results:

    • Most acoustic parameters demonstrated effectiveness for gender recognition.
    • A within-gender and within-subject averaging technique proved important for template generation.
    • The Euclidean distance measure was found to be robust and simple.
    • One recognition scheme achieved 100% correct classification on a database of 52 speakers.

    Conclusions:

    • Gender information in speech appears to be time-invariant, phoneme-independent, and speaker-independent.
    • Digital speech processing and pattern recognition offer a viable approach for automatic gender classification.
    • Specific acoustic features, particularly in vowels, are key discriminators of speaker gender.