Abstract: The present disclosure provides compositions and methods relating to the use of stents treated with therapeutic biologics for the treatment of cardiovascular diseases and conditions. In particular, the present disclosure provides novel compositions and methods for conjugating therapeutic extracellular vesicles to a stent to not only regulate vascular remodeling and inflammation, but also promote the regeneration of the injured tissue.

Abstract: A convertor computing device operable to reduce cross-border traffic over a network is provided. The convertor computing device is configured to store institution profile data associated with an institution and user profile data for a plurality of users associated with the institution. The convertor computing device is also configured to generate, based on the user profile data, sets of transfer data, each set identifying a recipient, associated recipient country, and transfer amount from a user. The convertor computing device is also configured to aggregate individual transfer amounts into a batch transfer amount based on matching recipient country, transfer the batch transfer amount in a single cross-border transaction from an institution account to a batch receiver in the matching country, and generate an instruction data file that instructs the batch receiver to distribute the individual transfer amounts to the associated recipients within the matching country.

Abstract: A system and related method identify a weakness of a workflow in a complex system. The method collects runtime data about the complex system. The complex system comprises a plurality of subcomponents, and the method identifies an abnormal operation in the complex system. The method constructs a multi-dimensional cause-and-effect relation matrix among the plurality of subcomponents, and filters one or more related operations using the multi-dimensional cause-and-effect relation matrix.

Abstract: This application discloses a data writing method, device, a storage server and a computer readable storage medium, including: writing, when a write request is received, write data corresponding to the write request to a write buffer; acquiring historical access data of a data block corresponding to to-be-flushed data in the write buffer when a data flushing operation is triggered for the write buffer; determining whether the to-be-flushed data is write-only data based on the historical access data by using a pre-trained classifier; if yes, writing the to-be-flushed data to a hard disk drive; and if no, writing the to-be-flushed data to a cache. The data writing method provided by this application can effectively reduce the traffic of writing dirty data to the cache while reserving more space in the cache for the ordinary data, thereby improving the utilization of the cache space and the read hit rate of the cache.

Abstract: A method includes receiving audio data encoding an utterance spoken by a native speaker of a first language, and receiving a biasing term list including one or more terms in a second language different than the first language. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data to generate speech recognition scores for both wordpieces and corresponding phoneme sequences in the first language. The method also includes rescoring the speech recognition scores for the phoneme sequences based on the one or more terms in the biasing term list, and executing, using the speech recognition scores for the wordpieces and the rescored speech recognition scores for the phoneme sequences, a decoding graph to generate a transcription for the utterance.

Abstract: A method of performing speech recognition using a two-pass deliberation architecture includes receiving a first-pass hypothesis and an encoded acoustic frame and encoding the first-pass hypothesis at a hypothesis encoder. The first-pass hypothesis is generated by a recurrent neural network (RNN) decoder model for the encoded acoustic frame. The method also includes generating, using a first attention mechanism attending to the encoded acoustic frame, a first context vector, and generating, using a second attention mechanism attending to the encoded first-pass hypothesis, a second context vector. The method also includes decoding the first context vector and the second context vector at a context vector decoder to form a second-pass hypothesis.

Abstract: A method of text-only and semi-supervised training for deliberation includes receiving training data including unspoken textual utterances that are each not paired with any corresponding spoken utterance of non-synthetic speech, and training a deliberation model that includes a text encoder and a deliberation decoder on the unspoken textual utterances. The method also includes receiving, at the trained deliberation model, first-pass hypotheses and non-causal acoustic embeddings. The first-pass hypotheses is generated by a recurrent neural network-transducer (RNN-T) decoder for the non-causal acoustic embeddings encoded by a non-causal encoder. The method also includes encoding, using the text encoder, the first-pass hypotheses generated by the RNN-T decoder, and generating, using the deliberation decoder attending to both the first-pass hypotheses and the non-causal acoustic embeddings, second-pass hypotheses.

Abstract: A method of performing speech recognition using a two-pass deliberation architecture includes receiving a first-pass hypothesis and an encoded acoustic frame and encoding the first-pass hypothesis at a hypothesis encoder. The first-pass hypothesis is generated by a recurrent neural network (RNN) decoder model for the encoded acoustic frame. The method also includes generating, using a first attention mechanism attending to the encoded acoustic frame, a first context vector, and generating, using a second attention mechanism attending to the encoded first-pass hypothesis, a second context vector.

Abstract: A method includes receiving an initial alignment for a candidate hypothesis generated by a transducer decoder model during a first pass. Here, the candidate hypothesis corresponds to a candidate transcription for an utterance and the initial alignment for the candidate hypothesis includes a sequence of output labels. Each output label corresponds to a blank symbol or a hypothesized sub-word unit. The method also include receiving a subsequent sequence of audio encodings characterizing the utterance. During an initial refinement step, the method also includes generating a new alignment for a rescored sequence of output labels using a non-autoregressive decoder. The non-autoregressive decoder is configured to receive the initial alignment for the candidate hypothesis and the subsequent sequence of audio encodings.

Abstract: A method includes receiving a sequence of acoustic frames and generating, by a first encoder, a first higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The method also includes generating, by a first pass transducer decoder, a first pass speech recognition hypothesis for a corresponding first higher order feature representation and generating, by a text encoder, a text encoding for a corresponding first pass speech recognition hypothesis. The method also includes generating, by a second encoder, a second higher order feature representation for a corresponding first higher order feature representation. The method also includes generating, by a second pass transducer decoder, a second pass speech recognition hypothesis using a corresponding second higher order feature representation and a corresponding text encoding.

Abstract: A method includes receiving a speech recognition result, and using a confidence estimation module (CEM), for each sub-word unit in a sequence of hypothesized sub-word units for the speech recognition result: obtaining a respective confidence embedding that represents a set of confidence features; generating, using a first attention mechanism, a confidence feature vector; generating, using a second attention mechanism, an acoustic context vector; and generating, as output from an output layer of the CEM, a respective confidence output score for each corresponding sub-word unit based on the confidence feature vector and the acoustic feature vector received as input by the output layer of the CEM. For each of the one or more words formed by the sequence of hypothesized sub-word units, the method also includes determining a respective word-level confidence score for the word. The method also includes determining an utterance-level confidence score by aggregating the word-level confidence scores.

Abstract: A method includes receiving a speech recognition result, and using a confidence estimation module (CEM), for each sub-word unit in a sequence of hypothesized sub-word units for the speech recognition result: obtaining a respective confidence embedding that represents a set of confidence features; generating, using a first attention mechanism, a confidence feature vector; generating, using a second attention mechanism, an acoustic context vector; and generating, as output from an output layer of the CEM, a respective confidence output score for each corresponding sub-word unit based on the confidence feature vector and the acoustic feature vector received as input by the output layer of the CEM. For each of the one or more words formed by the sequence of hypothesized sub-word units, the method also includes determining a respective word-level confidence score for the word. The method also includes determining an utterance-level confidence score by aggregating the word-level confidence scores.

Abstract: A method includes receiving audio data encoding an utterance spoken by a native speaker of a first language, and receiving a biasing term list including one or more terms in a second language different than the first language. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data to generate speech recognition scores for both wordpieces and corresponding phoneme sequences in the first language. The method also includes rescoring the speech recognition scores for the phoneme sequences based on the one or more terms in the biasing term list, and executing, using the speech recognition scores for the wordpieces and the rescored speech recognition scores for the phoneme sequences, a decoding graph to generate a transcription for the utterance.

Abstract: A method includes receiving audio data encoding an utterance spoken by a native speaker of a first language, and receiving a biasing term list including one or more terms in a second language different than the first language. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data to generate speech recognition scores for both wordpieces and corresponding phoneme sequences in the first language. The method also includes rescoring the speech recognition scores for the phoneme sequences based on the one or more terms in the biasing term list, and executing, using the speech recognition scores for the wordpieces and the rescored speech recognition scores for the phoneme sequences, a decoding graph to generate a transcription for the utterance.

Abstract: A method of performing speech recognition using a two-pass deliberation architecture includes receiving a first-pass hypothesis and an encoded acoustic frame and encoding the first-pass hypothesis at a hypothesis encoder. The first-pass hypothesis is generated by a recurrent neural network (RNN) decoder model for the encoded acoustic frame. The method also includes generating, using a first attention mechanism attending to the encoded acoustic frame, a first context vector, and generating, using a second attention mechanism attending to the encoded first-pass hypothesis, a second context vector.

Abstract: An electrical connector is provided for a mating connector to be inserted thereto. The electrical connector includes an insulating body having a tongue, and multiple terminals. A middle grounding sheet is located between the terminals in upper and lower rows, and has at least one first through hole. Each of left and right sides of the middle grounding sheet has a latch slot and a notch. The insulating body has a first insulating post entering the first through hole and a second insulating post entering the notch. A dimension of the second insulating post is larger than a dimension of the first insulating post. A metal shell frames outside the insulating body to form an insertion space. A first clearance between a first protruding portion and a shielding casing of the mating connector is more than or equal to 0.001 mm and less than or equal to 0.0449 mm.

Abstract: A method includes receiving audio data encoding an utterance spoken by a native speaker of a first language, and receiving a biasing term list including one or more terms in a second language different than the first language. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data to generate speech recognition scores for both wordpieces and corresponding phoneme sequences in the first language. The method also includes rescoring the speech recognition scores for the phoneme sequences based on the one or more terms in the biasing term list, and executing, using the speech recognition scores for the wordpieces and the rescored speech recognition scores for the phoneme sequences, a decoding graph to generate a transcription for the utterance.

Abstract: According to embodiments, a derived cache that is derived from a first instance of particular data is used to speed up queries and other operations over a second instance of the particular data. Traditionally, a DBMS generates and uses derived cache data only for the database data from which the derived data was derived. However, according to embodiments, derived cache data associated with a first instance of database data is relocated to the location of a second, newly created, instance of the database data. Since the derived cache data is derived from an identical copy of the database data, the cache data derived for the first instance can successfully be used to speed up applications running over the second instance of the database data.

Abstract: An electrical connector is provided for a mating connector to be inserted thereto. The electrical connector includes an insulating body having a tongue, and multiple terminals. A middle grounding sheet is located between the terminals in upper and lower rows, and has at least one first through hole. Each of left and right sides of the middle grounding sheet has a latch slot and a notch. The insulating body has a first insulating post entering the first through hole and a second insulating post entering the notch. A dimension of the second insulating post is larger than a dimension of the first insulating post. A metal shell frames outside the insulating body to form an insertion space. A first clearance between a first protruding portion and a shielding casing of the mating connector is more than or equal to 0.001 mm and less than or equal to 0.0449 mm.

Abstract: An electrical connector includes an insulation body, at least one first terminal and at least one second terminal, and a middle grounding plate. The insulation body has a base and a tongue located in a front end of the base. The first terminal and the second terminal are arranged in the base in an upper row and a lower row, and exposed to an upper surface and a lower surface of the tongue. The middle grounding plate has a body portion fixed to the tongue, and located between the first terminal and the second terminal, the first terminal has a first front edge, the second terminal has a second front edge, and the first front edge, the second front edge and an edge in a front end of the body portion are located in a same vertical plane.