Abstract: A method and apparatus for translating speech are provided. The method may include: recognizing received to-be-recognized speech of a source language to obtain a recognized text; concatenating the obtained recognized text after a to-be-translated text, to form a concatenated to-be-translated text; inputting the concatenated to-be-translated text into a pre-trained discriminant model to obtain a discrimination result for characterizing whether the concatenated to-be-translated text is to be translated, where the discriminant model is used to characterize a corresponding relationship between a text and a discrimination result corresponding to the text; in response to the positive discrimination result being obtained, translating the concatenated to-be-translated text to obtain a translation result of a target language, and outputting the translation result.

Abstract: Presented herein are embodiments of a prefix-to-prefix framework for simultaneous translation that implicitly learns to anticipates in a single translation. Within these frameworks are effective “wait-k” policy model embodiments that may be trained to generate a target sentence concurrently with a source sentence but lag behind by a predefined number of words. Embodiments of the prefix-to-prefix framework achieve low latency and better quality when compared to full-sentence translation in four directions: Chinese?English and German?English. Also presented herein is a novel latency metric that addresses deficiencies of previous latency metrics.

Abstract: Embodiments of the present disclosure provide a language conversion method and apparatus based on syntactic linearity and a non-transitory computer-readable storage medium. The method includes: encoding a source sentence to be converted by using a preset encoder to determine a first vector and a second vector corresponding to the source sentence; determining a current mask vector according to a preset rule, in which the mask vector is configured to modify vectors output by the preset encoder; determining a third vector according to target language characters corresponding to source characters located before a first source character; and decoding the first vector, the second vector, the mask vector, and the third vector by using a preset decoder to generate a target character corresponding to the first source character.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for translating a polysemy, and a medium. The method includes: obtaining a source language text; identifying and obtaining the polysemy from the source language text; inquiring related words corresponding to each interpretation of the polysemy; determining a target interpretation corresponding to the related words contained in the source language text; and translating the polysemy into the target interpretation.

Abstract: The present disclosure provides an end-to-end model training method and apparatus, which relates to a field of artificial intelligence technologies. The method includes: obtaining training data containing a plurality of training samples, in which the plurality of training samples include an original sequence, a target sequence and a corresponding tag list, the tag list includes importance tags in the target sequence and avoidance tags corresponding to the importance tags, and the avoidance tags are irrelevant tags corresponding to the importance tags; and adopting the training data to train a preset end-to-end model until a value of a preset optimization target function is smaller than a preset threshold.

Abstract: The present disclosure provides a method, apparatus, electronic device and readable storage medium for translation and relates to translation technologies. In the embodiments of the present disclosure, the at least one knowledge element is obtained according to associated information of content to be translated, and respective knowledge element in the at least one knowledge element comprise an element of the first language type and an element of the second language type so that the at least one knowledge element can be used to obtain a translation result of the content to be translated. Since the at least one knowledge element obtained in advance is taken as global information of the translation task of this time, it can be ensured that the translation result of the same content to be translated is consistent, thereby improving the quality of the translation result.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for evaluating a translation quality. The method may include: acquiring a to-be-evaluated translation and a reference translation; inputting the to-be-evaluated translation and the reference translation into a pre-trained repetition coding model to obtain a semantic similarity between the to-be-evaluated translation and the reference translation, the repetition coding model being a neural network for calculating a probability of a pair of sentences being repetition sentences; analyzing the to-be-evaluated translation and the reference translation into two syntax trees respectively; calculating a similarity between the two syntax trees as a text similarity between the to-be-evaluated translation and the reference translation; and using a weighted sum of the semantic similarity and the text similarity as a translation quality score.

Abstract: A method and apparatus for translating speech are provided. The method may include: recognizing received to-be-recognized speech of a source language to obtain a recognized text; concatenating the obtained recognized text after a to-be-translated text, to form a concatenated to-be-translated text; inputting the concatenated to-be-translated text into a pre-trained discriminant model to obtain a discrimination result for characterizing whether the concatenated to-be-translated text is to be translated, where the discriminant model is used to characterize a corresponding relationship between a text and a discrimination result corresponding to the text; in response to the positive discrimination result being obtained, translating the concatenated to-be-translated text to obtain a translation result of a target language, and outputting the translation result.

Abstract: Embodiments of the present disclosure disclose a text translation method, a text translation apparatus, a device and a storage medium. The method includes: obtaining a source language text; and translating the source language text with a modified translation model to obtain a target language text corresponding to the source language text, the modified translation model being obtained by modifying an original translation model based on a text evaluation result of one or more translated texts for training, the translated text for training being an output result after translating through the original translation model, and the text evaluation result for evaluating a contextual semantic relation in the translated text for training.

Abstract: A vibration control system for an unmanned aerial vehicle (UAV) is disclosed. The system includes a base platform fixedly coupled to a UAV structure, a working platform coupled to the base platform by two or more cables at two or more connection points on the working platform, and two or more actuators positioned either on the base platform or the working platform, each actuator configured to receive a signal to adjust tension in a corresponding cable, wherein by adjusting tension in the two or more cables, natural frequency of the working platform can be adjusted in response to frequency of vibration experienced by the working platform in order to maintain a frequency ratio (FR) of the vibration frequency to the natural frequency at or above a predetermined value.

Abstract: The present disclosure provides a translation processing method, a translation processing device, and a device. The first speech signal of the first language is obtained, and the speech feature vector of the first speech signal is extracted based on the preset algorithm. Further, the speech feature vector is input into the pre-trained end-to-end translation model for conversion from the first language speech to the second language text for processing, and the text information of the second language corresponding to the first speech signal is obtained. Moreover, speech synthesis is performed on the text information of the second language, and the corresponding second speech signal is obtained and played.

Abstract: Presented herein are embodiments of a prefix-to-prefix framework for simultaneous translation that implicitly learns to anticipates in a single translation. Within these frameworks are effective “wait-k” policy model embodiments that may be trained to generate a target sentence concurrently with a source sentence but lag behind by a predefined number of words. Embodiments of the prefix-to-prefix framework achieve low latency and better quality when compared to full-sentence translation in four directions: Chinese?English and German?English. Also presented herein is a novel latency metric that addresses deficiencies of previous latency metrics.

Abstract: A vibration control system for an unmanned aerial vehicle (UAV) is disclosed. The system includes a base platform fixedly coupled to a UAV structure, a working platform coupled to the base platform by two or more cables at two or more connection points on the working platform, and two or more actuators positioned either on the base platform or the working platform, each actuator configured to receive a signal to adjust tension in a corresponding cable, wherein by adjusting tension in the two or more cables, natural frequency of the working platform can be adjusted in response to frequency of vibration experienced by the working platform in order to maintain a frequency ratio (FR) of the vibration frequency to the natural frequency at or above a predetermined value.

Abstract: Described herein are extended release formulations of veliparib, ways to make them, and methods of treating cancer using them.

Abstract: A semantic similarity evaluation method includes performing word vectorization processing separately on words in a first sentence and a word in a second sentence to obtain a first word vector and a second word vector; performing, in a preset word vector compression order, compression coding processing on the first word vector according to a first compression coding parameter to obtain a first statement vector; performing, in the preset word vector compression order, compression coding processing on the second word vector according to a second compression coding parameter to obtain a second statement vector; and determining a vector distance between the first statement vector and the second statement vector, and evaluating a semantic similarity between the first sentence and the second sentence according to the vector distance. The method is used to evaluate a semantic similarity.

Abstract: A semantic similarity evaluation method includes performing word vectorization processing separately on words in a first sentence and a word in a second sentence to obtain a first word vector and a second word vector; performing, in a preset word vector compression order, compression coding processing on the first word vector according to a first compression coding parameter to obtain a first statement vector; performing, in the preset word vector compression order, compression coding processing on the second word vector according to a second compression coding parameter to obtain a second statement vector; and determining a vector distance between the first statement vector and the second statement vector, and evaluating a semantic similarity between the first sentence and the second sentence according to the vector distance. The method is used to evaluate a semantic similarity.

Abstract: A method and apparatus for suppressing subsequent re-request of a location request, for example a MO-LR request in a GSM communication system, by a mobile station (MS) (110) to the network. The method in the mobile station comprises transmitting (302) a location request message to a network. Then, at the MS, determining (304) that the network can not provide the requested location information. Creating (306) an indicator in a memory of the device that the network is not capable of providing the requested location information and finally suspending (308) subsequent transmission of location request message to the network.