Speech recognition result correction method, device, equipment and storage medium
A speech recognition and text recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve the problem that the accuracy of acoustic model recognition needs to be further improved, and achieve the effect of improving the accuracy.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0030] figure 1 It is a flow chart of a speech recognition result correcting method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of correcting speech recognition results, and the method can be executed by the speech recognition result correcting device provided in the embodiment of the present invention , the device may be implemented in software and / or hardware, and the device may be integrated in the terminal device or in an application end of the terminal device. Wherein, the terminal device may be, but not limited to, a mobile terminal (tablet computer or smart phone).
[0031] Wherein, the application end may be a plug-in of a certain client embedded in the terminal device, or a plug-in of the operating system of the terminal device, and the speech recognition result embedded in the terminal device may correct the operation of the client or the terminal device. The voice recognition result correction application progra...
Embodiment 2
[0044] Figure 2A It is a flow chart of a method for correcting speech recognition results provided by Embodiment 2 of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiments. In this embodiment, the step is to further use the neural machine translation NMT model to identify and correct the initial text information, and the final text recognition result is optimized as follows: the initial text information contains The text is segmented to obtain at least one word; the word is encoded into a dense vector by the encoder in the NMT model, and the dense vector is decoded by the decoder in the NMT model to obtain the final text recognition result.
[0045] Correspondingly, such as Figure 2A As shown, the method of this embodiment specifically includes:
[0046] S201. Perform speech recognition on the acquired speech data to obtain initial text information.
[0047] S202. Segment the text included in the initial text information to ob...
Embodiment 3
[0055] Figure 3A It is a flow chart of a method for correcting speech recognition results provided by Embodiment 3 of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiments. In this embodiment, further steps are to encode words into dense vectors through the encoder in the NMT model, and decode the dense vectors through the decoder in the NMT model to obtain The final text recognition result is optimized as follows: convert at least one word into a source hidden state vector through the encoder in the NMT model; input the source hidden state vector into the decoder in the NMT model, and output the target hidden state vector through the decoder in the NMT model State vector; determine the hidden state vector of the attention mechanism according to the target hidden state vector and the source hidden state vector; obtain the final text recognition result according to the hidden state vector of the attention mechanism.
[0056] Corre...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More - R&D
- Intellectual Property
- Life Sciences
- Materials
- Tech Scout
- Unparalleled Data Quality
- Higher Quality Content
- 60% Fewer Hallucinations
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com



