33 results about "Random text" patented technology

A cipher method for verifying a decryption of an encrypted user data key used to encrypt user data prior to an encryption of the user data key with an encryption key. The cipher method involves a decryption of the encrypted user data key with a decryption key in response to an initiation of a decryption of the encrypted user data with the user data key as decrypted with the description key, a decryption of the verification text with the user data key as decrypted with the decryption key, and a validation / invalidation of a use of the user data key as decrypted with the decryption key to decrypt the encrypted user data in response to a matched / unmatched comparison of the verification text as decrypted with the user data key and an intermixing of a known text and a random text.

A HRPD network access authentication method based on CAVE algorithm is provided. An AT (Access Terminal) generates a random number “RAND” necessary for a calculation of an AUTH1 by using a “Random text” included in the CHAP Challenge message. A UIM (User Identity Module) card works out the AUTH1 by using the random number “RAND” and an SSD_A (Shared Secret Data A) in the UIM card. The AT carries the AUTH1 in a Result field of the CHAP Response message. An AN-AAA (Access Network-Authentication, Authorization, and Accounting) generates the random number “RAND” necessary for the calculation of an AUTH2 by using a “Random text” included in a Radius Access Request message. The AN-AAA works out the AUTH2 by using the random number “RAND”. The two results AUTH1 and AUTH2 are compared. If the results are the same, the authentication on the AT passes. Otherwise, AT access is rejected.

Disclosed are a speech recognition verification device and a speech recognition verification method, which verify speech recognition results by executing artificial intelligence (AI) algorithms and / or machine learning algorithms in a 5G environment connected for Internet-of-Things. According to an embodiment, the speech recognition verification method includes converting a verification target text item to a verification target spoken utterance by applying a preset utterance condition, analyzing the verification target spoken utterance and outputting a recognition result text item corresponding to an analysis result, and verifying speech recognition performance through comparison between the verification target text item and the recognition result text item. According to the present disclosure, the speech recognition result may be verified objectively by using a spoken utterance generated with random text and various utterance conditions as input of speech recognition.

The present invention relates to the communication field and provides a verification method. A verification code server receives a verification code acquisition request sent by a client; generates and saves a system verification code; wherein the system verification code is determined by a string of random text; and encodes the system verification code Generate k verification code pictures from n original pictures; among them, k and n are integers greater than or equal to 2, and k is less than or equal to n; send k verification code pictures to the client; receive the verification request sent by the client , the verification request carries the verification code entered by the user according to the k verification code pictures; according to the system verification code, determine whether the verification code entered by the user is correct. Through the above solution, the randomly generated system verification code is encoded into n original pictures, which not only increases the difficulty of machine recognition, but also ensures the security of the verification code.

The present invention proposes a performance testing system for a large-scale multi-keyword precise matching algorithm, the system includes the following modules: a test data generation module, specifically: a random keyword generation submodule, a random text data generation submodule; Text generation sub-module; keyword set preprocessing performance testing module, specifically including: matching algorithm preprocessing interface call sub-module, test information generation sub-module. The invention solves the problem of interface standards and interoperable access between different network information security devices, realizes the cooperative work and linkage among them, and finally realizes the seamless integration of various network information security devices. It can test the performance indicators of various multi-keyword exact matching algorithms.

The invention relates to a method for improving rejection capability of a speech recognition system. The method comprises the following steps of collecting various types of noise data; classifying according to the noise types; for different types of noise, respectively training GMMs (Gauss mixed model); assembling various types of GMMs into an integral absorption model; training a statistic language model by various types of relatively random texts, and then establishing a recognition network by WFST (weighted finite state transducer) technique, which is called as an absorption network; connecting the absorption network, the absorption model and an original decoding network in parallel to form a new decoding network; enabling the input original audio frequency to pass endpoint detection and a feature extraction module, so as to generate feature vectors; and competing the feature vectors in the three parts of the decoding network according to an Viterbi algorithm, so as to generate a final recognition result, and effectively reject the noise and an out-of-vocabulary condition. The method has the advantage that on the premise of balancing the recognition efficiency, the effect of rejecting the out-of-vocabulary condition and the invalid input is well realized.

The invention discloses a sound selection method for waveform concatenation speech synthesis. The method comprises the following steps of: on the basis of an original audio, carrying out hidden markov based model training so as to obtain an acoustic model set and a corresponding characteristic decision tree; inputting a plurality of training texts and on the basis of the characteristic decision tree, searching to obtain related acoustic models so as to obtain corresponding target voice and target syllables; according to similarity of the target voice and corresponding candidate primitives and likelihood probability of each acoustic parameter of the candidate primitives under a current acoustic model, training to obtain a similarity classifier; inputting a random text to be synthesized, removing the dissimilar candidate primitives on the basis of the similarity classifier, selecting the optimal primitive from the residual candidate primitives by utilizing a concatenation cost minimization rule and carrying out concatenation to obtain synthetic speech. The adoption of the method disclosed by the invention can synthesize speech with higher tone quality.

The invention relates to a text line recognition method and device, a readable storage medium and electronic equipment. Wherein, the text line recognition method includes: inputting at least one text line image to be detected into a preset neural network model, and obtaining a detection result output by the preset neural network model, and the detection result is a character string in the text line image to be detected . Wherein, the preset neural network model is trained by using synthetic image samples as training samples. A synthetic image sample includes: samples, positive samples, difficult negative samples, and normal negative samples. In the technical solution provided by the present invention, by using synthetic image samples including samples, positive samples, difficult negative samples, and common negative samples as training samples of the preset neural network, the training samples of the preset neural network are associated image data, Thus, more supervision information is introduced, and compared with using independent random text line images as training data for training, the training effect of the preset neural network model is improved.

The invention provides a method and a device for displaying page characters. The method includes segmenting to-be-displayed characters to acquire N character groups, wherein N is a positive integer more than 2; mixing random characters in each character group; taking each character group after the random characters are mixed therein as a Dom node for splicing according to a corresponding sequence of segmenting; hiding the mixed-in random characters by setting patterns. A mixing mode is adopted, so that normal displaying of the page characters is guaranteed, webpage content acquired by copying and capturing is enabled not to be normally displayed due to the fact that the random characters are mixed in, freeness from dependence on a browser is realized by the mode, and the webpage characters are effectively prevented from being copied and captured maliciously.