Automatic Selection of Speech Data based on Confidence Measure

  • Authors

    • Mustafa Abdallah
    • Abdullah M. Moussa
    • Sherif M. Abdou
    • Mohsen Rashwan
    • Hassanin Al-Barhamtoshy
    https://doi.org/10.14419/ijet.v8i1.11.28186
  • data selection, confidence measure, speech processing, posterior probabilities, machine learning

  • Abstract

    The amount of training data used in automatic speech recognition and pronunciation aiding systems is one of the most important factors that can significantly affect the quality of the resulting systems. However, as the amount of training data increases, a huge effort in transcribing the data by professional linguists is needed. This task is usually expensive in terms of time and money. In this paper, we present an algorithm to automatically select more accurate subsets of speech data with high accuracy. The suggested algorithm utilizes confidence measures and posterior probabilities to extract parts of the data based on a confidence score. Experimental results and comparisons with a manually verified selection process and a random selection process show that the proposed algorithm is Robust and effective

     

     

  • References

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  • How to Cite

    Abdallah, M., M. Moussa, A., M. Abdou, S., Rashwan, M., & Al-Barhamtoshy, H. (2019). Automatic Selection of Speech Data based on Confidence Measure. International Journal of Engineering & Technology, 8(1.11), 158-160. https://doi.org/10.14419/ijet.v8i1.11.28186

    Received date: 2019-03-03

    Accepted date: 2019-03-03