Prosodic labeling method, device and apparatus, and medium

Abstract

The application discloses a prosodic labeling method, device and apparatus, and a medium. The method comprises the following steps: acquiring a first acoustic feature, a first text feature and a firstprosodic labeling result corresponding to a sample audio; the first acoustic feature serving as input of an encoder in an end-to-end neural network, the first text feature serving as input of a decoder in the end-to-end neural network, the first prosodic labeling result serving as an output of the end-to-end neural network, and the end-to-end neural network is trained to obtain a trained end-to-end neural network; and when a second acoustic feature and a second text feature of a to-be-labelled rhythm are obtained, directly outputting a second prosodic labeling result by utilizing the trainedend-to-end neural network. According to the prosodic labeling method, the acoustic features and the corresponding text features are effectively fused, thereby improving the accuracy of prosodic labeling.

Description

technical field [0001] The present application relates to the technical field of speech synthesis, in particular to a prosody tagging method, device, equipment, and medium. Background technique [0002] The synthesized sound library generally includes a large number of high-quality recorded audio clips, corresponding transcribed texts, and prosodic annotations on the transcribed texts based on the prosodic information of the recorded audio clips. How to automatically and accurately carry out the prosodic labeling of the synthesized sound bank by computer has become an important technology in the field of speech synthesis. [0003] Existing technical solution 1: first use the pre-trained text prosody prediction model to predict the prosody information of the text, and then use the pre-recorded audio to authenticate and screen the predicted text prosody information, eliminate the incorrect prosody information, and keep the correct prosody information. prosodic information to ...

AI Technical Summary

Problems solved by technology

[0004] Solution 1 cannot finally filter out the correct prosodic information without reading according to the predicted prosodic rhythm of the text

Option 2 splits the internal connection between speech and text, and cannot achieve good prosodic labeling effect

Moreover, the prosodic labeling process in the existing solutions includes multiple stages of processing. The component construction of each stage requires rich domain knowledge. The design of the entire system is difficult and the implementation is complicated. The errors of each stage will be superimposed in the final stage, so that The resulting prosodic information is inaccurate

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