Method and system for speech quality perception evaluation based on speech semantic recognition technology
A technology for semantic recognition and speech quality, applied in the field of communication, can solve the problems such as the inability to restore the thinking paradigm of the human brain, and the poor repeatability of subjective evaluation methods, and achieve the effect of solving poor repeatability and precise positioning.
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2018-11-23
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Abstract
Description
technical field
[0001] The present invention relates to the communication field, in particular to voice services in the communication field, such as a network voice quality perception evaluation method related to 2G, Volte and network conversation voice (QQ and WeChat voice, etc.). Background technique
[0002] Voice services have always existed as the main business of operators from the analog network, GSM to today's 4G, and even in the future 5G era. When traditional services such as SMS and MMS have been eroded by OTT (over the top) service providers, voice services are The unique reliability and high QoS have been continuously used by everyone. However, users are not only satisfied with the acquisition of information when talking on mobile phones, but also pay more attention to the voice quality, whether it can restore the sound effect with high fidelity, and express human emotions. In this case, higher-definition voice is required to meet the demand. As an all-IP 4G v...
Examples
Embodiment Construction
[0169] Such as figure 1 As shown, the method for perceptual evaluation of speech quality based on speech semantic recognition technology specifically includes the following steps:
[0170] S1: Convert the voice and audio of the voice initiator into text information, and store the overall voice and audio information and the converted text information in the server for storage and simultaneously save the network parameters and event information of the voice initiator;
[0171] S2: Convert the voice and audio of the voice receiver into text information, and store the overall voice and audio information and the converted text information in the server for storage and at the same time save the network parameters and event information of the voice receiver;
[0172] S3: Evaluate the text similarity in step S1 and step S2 by using the method of text similarity, and display it in real time;
[0173] S4: Use the voice information to establish a user perception evaluation model through...