N optimal spoken language semantic recognition method and device and electronic equipment
A technology of semantic recognition and spoken language, which is applied in the field of electronic equipment and computer readable media, devices, and N-optimal spoken language semantic recognition methods, can solve problems that affect the dialogue effect between voice robots and users, user intention recognition errors, etc., and achieve improved intention Recognition accuracy and reduce the effect of user intent recognition errors
Active Publication Date: 2020-12-04
北京淇瑀信息科技有限公司
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Therefore, the existing ASR will make certain errors in the process of converting text, which will lead to the subsequent SLU misidentifying the user's intention and affecting the dialogue effect between the voice robot and the user.
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[0042] Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings, and although the exemplary embodiments may be embodied in many specific forms, these should not be construed as limited to the embodiments set forth herein. On the contrary, these exemplary embodiments are provided in order to make the content of the present invention more complete and more convenient to fully convey the inventive concept to those skilled in the art.
[0043] On the premise of complying with the technical concept of the present invention, the structure, performance, effect or other features described in a specific embodiment can be combined in any suitable way into one or more other embodiments.
[0044] During the introduction of specific embodiments, detailed descriptions of structures, performances, effects or other features are intended to enable those skilled in the art to fully understand the embodiments. However, it does no...
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The invention discloses an N optimal spoken language semantic recognition method and apparatus, and electronic equipment. The method comprises the steps: obtaining text data of first N probability values output to historical audio data by an automatic speech recognition ASR model and a label of each piece of text data as a training set; training a spoken language understanding SLU model through the training set; inputting the text data of the first M probability values output by the ASR model to the test audio data into the SLU model to obtain an intention recognition probability sequence of the M text data; and outputting the intention with the maximum probability in the intention recognition probability sequence as the intention of the test audio data. According to the method, the text data of the first few probability values of the ASR model are considered in both SLU model training and SLU model application, and then intention recognition is performed according to the text data ofthe first few probability values, so that user intention recognition errors caused by ASR recognition errors can be effectively reduced, and the intention recognition accuracy is improved.
Description
technical field [0001] The present invention relates to the technical field of speech intelligence, in particular to an N-optimal spoken language semantic recognition method, device, electronic equipment and computer-readable medium. Background technique [0002] With the development of artificial intelligence technology, the application of voice robots is becoming more and more extensive. Based on technologies such as speech recognition, speech synthesis, and natural language understanding, voice robots can provide enterprises with an intelligent human-computer interaction experience of "listening, speaking, and understanding" in various practical application scenarios. At present, voice robots have been widely used in telemarketing, intelligent Q&A, intelligent quality inspection, real-time speech subtitles, interview recording and other scenarios. [0003] The voice robot first performs natural speech understanding of the user's voice to identify the user's intention, an...
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IPC IPC(8): G10L15/06G10L15/14G10L15/16G10L15/183G06N3/04
CPCG10L15/06G10L15/063G10L15/183G10L15/16G10L15/142G06N3/049G06N3/047G06N3/045
Inventor 张常睿李蒙
Owner 北京淇瑀信息科技有限公司