Corpus ID: 222341658

Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification

@article{Rangan2020ExploitingSA,
  title={Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification},
  author={Pradeep Rangan and S. Teki and Hemant Misra},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.07130}
}
  • Pradeep Rangan, S. Teki, Hemant Misra
  • Published 2020
  • Computer Science, Engineering
  • ArXiv
  • Spoken language Identification (LID) systems are needed to identify the language(s) present in a given audio sample, and typically could be the first step in many speech processing related tasks such as automatic speech recognition (ASR). Automatic identification of the languages present in a speech signal is not only scientifically interesting, but also of practical importance in a multilingual country such as India. In many of the Indian cities, when people interact with each other, as many… CONTINUE READING
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    References

    SHOWING 1-10 OF 31 REFERENCES
    Spoken Language Identification using ConvNets
    • 6
    • PDF
    Language Identification Using Deep Convolutional Recurrent Neural Networks
    • 30
    • PDF
    Data augmentation for low resource languages
    • 81
    • PDF
    Language Identification of Assamese, Bengali and English Speech
    • 2
    • PDF
    Integrating Acoustic, Prosodic and Phonotactic Features for Spoken Language Identification
    • 65
    • PDF
    Language Recognition for Dialects and Closely Related Languages
    • 15
    • PDF
    Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin
    • 1,685
    • PDF
    Identification of Language using Mel-Frequency Cepstral Coefficients (MFCC)
    • 36
    Multilevel and Session Variability Compensated Language Recognition: ATVS-UAM Systems at NIST LRE 2009
    • 13
    • PDF