Method and device for synthesizing emotional speech of specific speaker under extremely low resources

Abstract

The invention discloses a method and a device for synthesizing emotional speech of a specific speaker under extremely low resources, computer equipment and a storage medium. The method comprises the following steps: acquiring a training text and an audio corresponding to the training text, converting the training text into a phoneme sequence, embedding a slot with an emotion vector to obtain initial training data, inputting into a deep learning model, training to obtain a base model, acquiring a specific text and a specific audio, converting the specific text into a corresponding phoneme sequence, embedding a slot with an emotion vector into the phoneme sequence to obtain specific training data, inputting the specific training data into the base model, training to obtain a speech synthesismodel, converting a to-be-synthesized text into a phoneme sequence to obtain a to-be-synthesized phoneme sequence, filling the to-be-synthesized phoneme sequence into the emotion slot to obtain synthetic input data, and inputting the synthetic input data into the speech synthesis model to obtain a speech audio with specific emotion, so as to reduce the cost of obtaining the speech audio with thespecific emotion and improve the flexibility of an emotion speech synthesis scheme.

Description

technical field [0001] The present invention relates to the technical field of speech signal processing, in particular to a speech synthesis method, device, computer equipment and storage medium for specific speaker emotion under extremely low resources. Background technique [0002] Speech synthesis technology is to give computers (or various terminal devices) the ability to speak like humans, which is a typical interdisciplinary subject. TTS technology (also known as text-to-speech technology) belongs to speech synthesis, which is a technology that converts text information generated by the computer itself or externally input into intelligible and fluent speech output. Emotional speech synthesis is a research field that has only emerged in the past ten years. Compared with traditional speech synthesis, emotional speech synthesis takes into account the speaker's emotional state and speaking style, making the synthesized speech more intelligent and humanized, with more Wide...

AI Technical Summary

Problems solved by technology

The advantage of the neural network synthesis method is that the processing is simple and the synthesis effect is very natural. The disadvantage is that a large data set is required to train the model, especially for the labeling of emotional data, the cost is too high

It can be seen that traditional emotional speech synthesis solutions often have limitations and high costs

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