Improved diva neural network model pronunciation method based on vocal tract action knowledge base

A neural network model and knowledge base technology, which is applied in the field of pronunciation of the improved DIVA neural network model based on the vocal tract action knowledge base, can solve the problems of rough description and inability to coexist at the same time, and achieve the effect of reducing the number of trainings and improving the accuracy of pronunciation.

Inactive Publication Date: 2016-06-08
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0011] There are some defects in the DIVA model, which are mainly manifested in the following points: For the model, it is assumed that all state information given at a given point is available instantaneously; the model is assumed to have no neural delay and the system uses instantaneous feedback control; The reference frame for control can only choose the sensory reference frame space of the articulation organ or the auditory space reference frame, and the two cannot coexist at the same time; the description of the segmentation of cortical and subcortical processing and the correlation of brain region components is relatively rough

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  • Improved diva neural network model pronunciation method based on vocal tract action knowledge base
  • Improved diva neural network model pronunciation method based on vocal tract action knowledge base
  • Improved diva neural network model pronunciation method based on vocal tract action knowledge base

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[0031] Below in conjunction with accompanying drawing, the technical scheme of invention is described in detail:

[0032] figure 2 A block diagram of the vocal tract action knowledge base model is given in . The vocal tract movement knowledge base includes sensory-motor, speaking skills and comparable mental syllabary.

[0033] The workflow of the vocal tract action knowledge base model is divided into two stages: speech generation and classification perception:

[0034] The workflow of the speech production stage is as follows: the activation of the vocal tract action knowledge base model starts with the activation of the phoneme representation of the phonetic item, and this speech mode is to process syllables one by one. In the case of processing high-frequency syllables, the model has captured the planned motion of high-frequency syllables, first the planned motion is activated through the phonetic map set, and then the corresponding vocal tract action of each syllable p...

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Abstract

The invention relates to an articulation method, in particular to an articulation method of a Directions Into of Articulators (DIVA) neural network model improved on the basis of a track action knowledge base. The articulation method is characterized in that the improved DIVA neural network model added with the track action knowledge base is adopted, and for voice not included in a voice mapping set, the corrected auditory feedback information is obtained by combining disturbance factors, the neural network is trained by aid of the corrected auditory feedback information, and therefore the training times of the model in articulation generation are reduced and articulation accuracy is improved.

Description

technical field [0001] The invention relates to a pronunciation method, in particular to an improved DIVA neural network model pronunciation method based on vocal tract action knowledge base. Background technique [0002] Neuro-computational speech model (Neuro-computational speech model) is a model that uses computer simulation to realize a series of complex processes such as speech generation, perception and acquisition. The composition of the neurocomputational speech model is very complex, including at least a cognitive part, a motor processing part and a sensory processing part: the role of the cognitive part is to generate neural activation (or generate phoneme representations) during the speech generation and speech perception stages; The motor processing part starts with the activation planning movement according to the generated phoneme representation, and ends with the movement of the vocal organs corresponding to the specific phoneme item; the sensory processing p...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/10G06N3/00
Inventor 张少白徐歆冰
Owner NANJING UNIV OF POSTS & TELECOMM
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