Abstract: The present disclosure relates to a computer-implemented method for electronic circuit design. Embodiments may include receiving, using at least one processor, data corresponding to an electronic design schematic. Embodiments may further include analyzing the data to learn one or more device size parameters, a range of parameters, or a matching relationship of parameters based upon, at least in part, the electronic design schematic or the electronic design layout, wherein analyzing occurs without user action.

Abstract: The present disclosure proposes a speech processing method and a cloud-based speech processing apparatus. The speech processing method includes: acquiring a piece of speech to be recognized collected by a terminal; performing a speech recognition on the piece of speech to be recognized; detecting whether the piece of speech to be recognized ends during the speech recognition; and feeding back a recognized result of the piece of speech to be recognized to the terminal when it is detected that the piece of speech to be recognized ends.

Abstract: According to embodiments of the present disclosure, a method, apparatus, device, and computer readable storage medium for voice interaction are provided. The method includes: determining a text corresponding to the voice signal based on a voice feature of a received voice signal. The method further includes: determining, based on the voice feature and the text, a matching degree between a reference voice feature of an element in the text and a target voice feature of the element. The method further includes: determining a first possibility that the voice signal is an executable command based on the text. The method further includes: determining a second possibility that the voice signal is the executable command based on the voice feature.

Abstract: The present disclosure provides a method and a device for recognizing a text segmentation position. The method includes: receiving a continuous voice message inputted by a user, and recognizing the continuous voice message to generate a text message corresponding to the continuous voice message; analyzing the text message to determine an interval position, and sequentially inserting a sentence end and sentence begin sign at each interval position; calculating a segmentation value corresponding to the sentence end and sentence begin sign inserted at a present interval position according to a preset algorithm; and determining whether the segmentation value is greater than a preset threshold, and determining the present interval position as a segmentation position when the segmentation value is greater than the preset threshold.

Abstract: The present disclosure relates to a computer-implemented method for electronic design is provided. Embodiments may include receiving, using at least one processor, an electronic design and determining an objective function associated with the electronic design. Embodiments may further include optimizing the objective function using Bayesian optimization and generating a best hyper-parameter setting based upon, at least in part, the Bayesian optimization.

Abstract: Embodiments included herein are directed towards method for electronic design. Embodiments may include receiving, using at least one processor, a placed layout and one or more electronic design simulation datasets including current information associated with at least one pin. Embodiments may further include estimating a width to support the current information associated with the at least one pin and updating a pin size associated with the at least one pin based upon, at least in part, the estimated width. Embodiments may also include identifying at least one pin that is above a predetermined threshold and splitting the at least one pin that is above the predetermined threshold into a plurality of pins. Embodiments may further include generating one or more width-spacing-pattern tracks for one or more internal nets based upon, at least in part, the updated pin size.

Abstract: The present disclosure discloses an interactive voice-control method and apparatus, a device and a medium. The method includes: obtaining a sound signal at a voice interaction device and recognized information that is recognized from the sound signal; determining an interaction confidence of the sound signal based at least on at least one of an acoustic feature representation of the sound signal and a semantic feature representation associated with the recognized information; determining a matching status between the recognized information and the sound signal; and providing the interaction confidence and the matching status for controlling a response of the voice interaction device to the sound signal.

Abstract: The present disclosure provides a speech data processing method and apparatus, a device and a storage medium, wherein the method comprises: a client obtains speech data, uses a speech wakeup engine to perform wakeup recognition for the obtained speech data, and stores the obtained speech data in a cyclic buffer queue; the client obtains a wakeup recognition result returned by the speech wakeup engine upon completion of the wakeup recognition, and if the wakeup recognition result is acknowledged wakeup and it is determined that there occurs a case of oneshot currently, determines an interception starting position and obtains buffer data in the cyclic buffer queue from the interception staring position to an end of the queue, the buffer data at least including the content to be recognized; the client sends the buffer data to a speech recognition engine so that the speech recognition engine performs speech recognition for the content to be recognized in the buffer data.

Abstract: A method, apparatus, device, and computer readable storage medium for recognizing and decoding a voice based on a streaming attention model are provided. The method may include generating a plurality of acoustic paths for decoding the voice using the streaming attention model, and then merging acoustic paths with identical last syllables of the plurality of acoustic paths to obtain a plurality of merged acoustic paths. The method may further include selecting a preset number of acoustic paths from the plurality of merged acoustic paths as retained candidate acoustic paths. Embodiments of the present disclosure present a concept that acoustic score calculating of a current voice fragment is only affected by its last voice fragment and has nothing to do with earlier voice history, and merge acoustic paths with the identical last syllables of the plurality of candidate acoustic paths.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for speech recognition. The method includes: determining, based on an acoustic score of a speech frame in a speech signal, a non-silence frame in the speech signal; determining a buffer frame between adjacent non-silence frames based on the acoustic score of the speech frame, a modeling unit corresponding to the buffer frame characterizing a beginning or end of a sentence; and decoding a speech frame after removing the buffer frame from the speech signal, to obtain a speech recognition result.

Abstract: The present disclosure proposes a method and an apparatus for converting English speech information into a text. The method may include: receiving the English speech information inputted by a user, determining a target speech recognition model according to a preset algorithm, and identifying original phonemes of the English speech information by applying the target speech recognition model; performing a matching on the original phonemes by applying a phonetic model generated by pre-training English texts and a preset probability model, and determining a target phoneme matched successfully; and acquiring a target English text corresponding to the target phoneme, and displaying the target English text on a speech conversion textbox.

Abstract: Embodiments of the present disclosure provide a method for controlling a smart device, a computer device and a non-transitory computer readable storage medium. The method includes performing speech recognition on a speech signal acquired by the smart device; determining whether a control instruction corresponding to the speech signal matches with a present operation scene of the smart device; and adjusting an operation state of the smart device according to the control instruction when the control instruction matches with the present operation scene.

Abstract: The present disclosure provides a speech recognition method and device. The method includes: receiving a speech signal; decoding the speech signal according to an acoustic model, a language model and a decoding network established in advance, and dynamically adding a blank unit in a decoding process to obtain an optimum decoding path with the added blank unit, in which the acoustic model is obtained based on connectionist temporal classification training, the acoustic model includes basic pronunciation units and the blank unit, and the decoding network includes a plurality of decoding paths consisting of the basic pronunciation units; and outputting the optimum decoding path as a recognition result of the speech signal.

Abstract: A method and system for building a speech recognizer, and a speech recognition method and system are proposed. The method for building a speech recognizer includes: reading and parsing each grammar file, and building a network of each grammar; reading an acoustic syllable mapping relationship table, and deploying the network of each grammar as a syllable network; performing a merge minimization operation for each syllable network to form a sound element decoding network; forming the speech recognizer by using the sound element decoding network and a language model. The technical solutions of the present disclosure may be applied to exhibit strong extensibility, support an N-Gram language model, support a class model, present flexible use, and adapt for an embedded recognizer in a vehicle-mounted environment.

Abstract: The present disclosure provides a wake-on-voice method, a terminal and a storage medium. The method includes: acquiring a wake-up voice configured to wake up a smart terminal; performing an analysis on an acoustic feature of the wake-up voice by using a preset acoustic model and a preset wake-up word recognition network of the smart terminal, so as to acquire a confidence coefficient of the acoustic feature of the wake-up voice with respect to an acoustic feature of a preset wake-up word; determining whether the confidence coefficient falls in a preset range of moderate confidence coefficients, if yes, uploading the wake-up voice to a remote server; and determining whether a linguistic feature obtained by analyzing the wake-up voice using a linguistic model matches to a linguistic feature of the preset wake-up word, if yes, receiving an instruction to wake up the smart terminal generated by the remote server.

Abstract: The present disclosure provides a method and a device for processing a speech based on artificial intelligence. The method includes: grading a current frame included in a speech packet to be decoded by using an acoustic model to obtain a grading result; identifying whether the current frame is a quasi-silent frame according the grading result; and skipping the current frame and not decoding the current frame if the current frame is the quasi-silent frame. In the present disclosure, before the current frame included in the speech pocket to be decoded is decoded, it is identified whether to decode the current frame according to the grading result obtained with the acoustic model. When there is no need to decode the current frame, the current frame is skipped. Thus, a redundancy decoding may be avoided, a speed of decoding is improved and recognition of the speech packet to be decoded is expedited.

Abstract: A container login method, a container login apparatus, and a storage medium are provided. In an example embodiment, a target container login request from a browser is received; a first connection between a server and the browser is established based on the target container login request; an address of a control node corresponding to a container cluster in which a target container is located is obtained based on an identifier of the container cluster; and a second connection between the server and the target container is established based on the address of the control node and an identifier of the target container, to log in to the target container.

Abstract: The present disclosure discloses a method including: performing a silence detection on a speech to be decoded; cutting the speech to be decoded off to obtain a target speech if detecting that the speech to be detected is a silent speech; resetting tail features of the target speech with preset tail features of silent frames; and performing a CTC decoding process on the target speech reset. In embodiments, when a large number of blank frames are carried in the speech to be decoded, the speech to be decoded is cut off, and the tail features of the target speech is placed with the tail features of the silent frames such that there may be one CTC peak when the CTC decoding process is performed on the tail features of the target speech. Therefore, a last word of text content may be displayed rapidly on a screen.

Abstract: An in-cloud wake-up method and system, a terminal and a non-volatile computer-readable storage medium are provided. The in-cloud wake-up method includes: receiving wake-up voice input by a user, and transmitting the wake-up voice to cloud; performing an decoding operation on the wake-up voice in cloud to generate a wake-up text; identifying wake-up characters in the wake-up text; and providing a wake-up instruction according to an identification result. With the in-cloud wake-up method, voice can be identified in cloud, and a smart device can be waken up in cloud according to the identified voice, so that resource consumption and power loss of the terminal device are reduced in the case of ensuring the quality of wake-up.

Abstract: The present utility model relates to a building structure, and in particular to a self-heat preservation building structure applied to extremely severe cold regions.