PATENT CLAIM ANALYSIS

Application Number: 15911114
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["704", "221000"]

Abstract:
Disclosed are a voice recognition system and a construction method for the voice recognition system. By way of layering the system, a general semantic recognition operation for the system is separated from a specific semantic recognition operation for an application program; and by way of classifying the application programs and abstracting out a common performance function, the system can find the application program matching the voice content semantics very efficiently and a third-party program is easily added into the existing voice recognition system. The present invention maps many performance function to a preset expression with semantic variables, so that the system can recognize more semantic expression manners with optimization of the semantic recognition. Therefore, the system can show more humanized characteristics.

Claim (Index 1):
A voice recognition system, comprising:\n a registration center storing information of application programs installed on the speech recognition system; wherein the registration center comprises: class nodes classified by intent, each class node stores preset expressions with semantic variables which describe common behaviors of a series of application programs, and the preset expressions are mapped to a public function set; wherein, the speech recognition system further comprising: application program joining the registration center by declaring a class node to which it belongs and inheriting the public function set of the class node; the application program is a third-party application program downloaded from an application store; and a voice recognition module converting voice input by user into text form; the speech recognition system selects the corresponding application program to process information obtained from text content according to the text content output by the voice recognition module; when the text content output by the voice recognition module matches with a preset expression with semantic variables of a class node in the registration center, the speech recognition system selects the application program belonging to the matching class node and writes the corresponding intent name and intent variables into the selected application program's private directory, the application program selects and executes a public function inherited from the matching class node based on the incoming intent name and variables after the application program is started; the intent name is bound to the matching preset expression with semantic variables and corresponds to a constant in the public function inherited from the matching class node; and the intent variables are extracted from the text content output by the voice recognition module and correspond to variables in the public function inherited from the matching class node; wherein when the text content output by the voice recognition module matches with a preset expression with semantic variables of a class node in the registration center, manners in which the speech recognition system selects the application program including at least: when the matching preset expression with semantic variables specifies an application name, the speech recognition system selects the application program according to the application name.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 1.91176
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14909741', '13515811', '12689629', '10316588', '15425099']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2229365489097487
- 35 USC 102 Novelty (BERT): 0.5435389283224454
- Combined Prediction Score: 0.2549967868510184
- Mean Citation Score: 220.927776
- Max Citation Score: 383.06448
- Similarity Product: 336.60177932373045

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test