Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210800246-6.doi: 10.11896/jsjkx.210800246

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Study on Quality Evaluation Method of Speech Datasets for Algorithm Model

LI Sun, CAO Feng, LIU Zi-shan   

  1. China Academy of Information and Communications Technology,Beijing 100191,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:LI Sun,born in 1988,postgraduate,engineer.Her main research interests include machine learning,perceptual cognitive technology and data governance,etc.
    LIU Zi-shan,born in 1992,Ph.D.Her main research interests include network intelligence,federated learning,data security and privacy,etc.

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Abstract: With the maturity of intelligent voice technology and product application,the demand for high-quality voice datasets is increasing.There have been some researchers put effort on the quality evaluation of the structured data,but there are few stan-dards appeared for the unstructured voice dataset.By analyzing the construction principle of speech algorithm model and analyzing the construction demand of voice dataset,a unified quality assessment framework for the voice dataset is presented.The framework proposes to evaluate the dataset in terms of four dimensions,each of which subsumes a set of criteria:breadth coverage,anthology distinction,field depth and accuracy completeness.The criteria that are suitable to evaluate the quality dimensions are presented,each with the definition,measurement method,and the evaluation process for the voice dataset quality measurement.Experimental assessment and analysis results of the voice datasets in the vehicular application field are presented as the reference for evaluating the voice dataset quality,and promoting the construction of the voice dataset.Considering the diversified applicabi-lity,privacy issues,efficiency requirements,automation requirements and other aspects of the construction of voice data sets,the development suggestions for building high-quality voice datasets are proposed.

Key words: Artificial intelligence, Speech dataset, Quality assessment, Algorithm, Model, Intelligent speech

CLC Number: 

  • TN912.34
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