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Speech translation method and device, device and storage medium

A speech translation and speech technology, which is applied in natural language translation, speech analysis, speech recognition, etc., can solve the problems of weak robustness of translation models, achieve the effects of improving robustness, reducing labor costs, and improving fault tolerance

Active Publication Date: 2022-07-12
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In the process of implementing the present invention, the inventor found that the prior art has the following defects: the translation model is not robust enough to obtain the correct translation result corresponding to the speech information based on the wrong speech recognition result

Method used

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  • Speech translation method and device, device and storage medium
  • Speech translation method and device, device and storage medium
  • Speech translation method and device, device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] figure 1 This is a flowchart of a speech translation method provided in Embodiment 1 of the present invention. The method in this embodiment can be executed by a speech translation device, which can be implemented by hardware and / or software, and can generally be integrated into equipment. , such as servers, etc. The method of this embodiment specifically includes:

[0030] S110. Acquire the speech recognition text of the speech to be translated.

[0031] In this embodiment, the speech to be translated specifically refers to the speech information that needs to be translated into the target language speech information. Specifically, the speech to be translated may be speech information of any language, and may be speech information of any language content, which is not limited in this embodiment.

[0032] Further, in this embodiment, the speech recognition text of the speech to be translated may be obtained specifically through a neural network with a speech recognit...

Embodiment 2

[0041] figure 2 This is a flowchart of a speech translation method provided in Embodiment 2 of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiment, and in this embodiment, a specific implementation manner of adding a translation model training step is given.

[0042] Correspondingly, the method of this embodiment specifically includes:

[0043] S210. Use the first type of speech recognition model to obtain the speech recognition result corresponding to the second type of speech recognition training corpus.

[0044] In this embodiment, the training steps of the translation model are added, that is, steps 210 to 240, so that the trained translation model has a high error tolerance for the speech recognition result.

[0045]In this embodiment, the first type of speech recognition model specifically refers to a speech recognition model trained by using the first type of speech recognition training corpus. The first type of speech ...

Embodiment 3

[0058] image 3 This is a flowchart of a speech translation method provided in Embodiment 3 of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiment. In this embodiment, a specific acquisition step of speech recognition results is given, a specific acquisition step of speech recognition correct and incorrect word pairs, and a specific acquisition of training corpus is provided. steps, and specific implementations of the training steps of the embodied translation model.

[0059] Correspondingly, the method of this embodiment specifically includes:

[0060] S310. Use a general speech recognition model to acquire speech recognition results corresponding to the special speech recognition training corpus.

[0061] In this embodiment, the first type of speech recognition model is specifically a general speech recognition model, and the second type of speech recognition training corpus is specifically a special speech recognition trainin...

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Abstract

Embodiments of the present invention disclose a speech translation method, device, device, and storage medium. The method includes: acquiring the speech recognition text of the speech to be translated; translating the speech recognition text with the translation model to obtain the target language text; the training corpus of the translation model at least includes the conventional training corpus and the noise training corpus, and the conventional training corpus and the noise training corpus Include correct words and incorrect words in speech recognition correct and incorrect word pairs, respectively. The technical solution of the embodiment of the present invention solves the technical defect that the translation model in the prior art has weak robustness, and it is difficult to obtain the correct translation result corresponding to the speech information according to the erroneous speech recognition result, so that there is an error in the speech recognition result. At the same time, the translation model can also obtain correct speech translation results, which improves the translation model's fault tolerance for speech recognition text, thereby improving the robustness of the translation model, and indirectly reducing the labor cost of checking the speech translation results.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of speech processing, and in particular, to a speech translation method and apparatus, device, and storage medium. Background technique [0002] In the traditional speech translation process, it is generally necessary to perform speech recognition first to generate the corresponding speech recognition text, then translate the speech recognition text into the target language text, and finally synthesize the target language text into the target speech information. In this series of technical links, due to factors such as on-site noise, the speaker is too far from the microphone, etc., the speech recognition results may be unstable, and some homophone recognition errors may easily occur. [0003] In the prior art, the speech recognition model generally acquires N speech recognition texts corresponding to the input speech information at the same time, and then selects the highest text from ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/232G06F40/58G10L15/26
CPCG10L15/26G06F40/232G06F40/58
Inventor 熊皓何中军李芝忻舟王海峰
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD