Speech recognition system for big data analysis

Abstract

In view of the problem that speech recognition is of low recognition rate in big data analysis, the invention discloses a speech recognition system for big data analysis. The system comprises a speech information classification module, an original speech processing module, an acoustic feature recognition and extraction module, a basic metadata set, an acoustic feature matching module, a recognition error correction module, and a result output module. The ability of the computer to clean and correct data in each stage of speech recognition is improved, and the processing result of speech recognition is more accurate.

Description

technical field [0001] The invention relates to the technical field of speech recognition, in particular to a speech recognition system for big data analysis. Background technique [0002] In recent years, speech recognition technology has made remarkable progress, and has moved from the laboratory to the market. In practical applications, such as the intelligent assistant Siri, by recognizing the user's voice input information, the interaction with the user is automatically completed. [0003] At present, when performing speech recognition, environmental noise has a great impact on the recognition rate of speech recognition. At the same time, the processing method of the original speech information will also have a certain impact on the recognition results. In addition, different people have pronunciation habits. The difference in speech recognition will be significantly affected by using a single acoustic feature for recognition. [0004] At the same time, different dial...

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Problems solved by technology

[0003] At present, when performing speech recognition, environmental noise has a great impact on the recognition rate of speech recognition. At the same time, the processing method of the original speech information will also have a certain impact on the recognition results. In addition, different people have pronunciation habits. The difference in speech recognition using a single acoustic feature will significantly affect the recognition rate of speech recognition

[0004] At the same time, different dialects have similar pronunciation characteristics and pronunciation habits. The emotion of the speaker will also affect the speech rate and sentence length, which will affect the recognition accuracy of acoustic features.

[0005] Because the recognition rate of speech recognition is not high enough, it is difficult to use speech for big data analysis

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