A facility for facilitating payments from a client to a freelancer is described. The facility provides a mobile app enabling the freelancer to open an account and solicit payments by clients. In response, each client can use any of a variety of forms of electronic payments to pay into the account. The freelancer can use a debit card issued for the account to spend or withdraw payments made into the account, and can use the app to track requests for payment, payments, client activity, and spending and withdrawals from the account.

A facility for facilitating payments from a client to a freelancer is described. The facility provides a mobile app enabling the freelancer to open an account and solicit payments by clients. In response, each client can use any of a variety of forms of electronic payments to pay into the account. The freelancer can use a debit card issued for the account to spend or withdraw payments made into the account, and can use the app to track requests for payment, payments, client activity, and spending and withdrawals from the account.

A machine translation method includes: an electronic device displays a first user interface, where source text content is displayed in the first user interface; after detecting an operation of triggering scrolling screenshot taking by a user, the electronic device automatically starts to take a scrolling screenshot; the electronic device obtains a first picture through scrolling screenshot taking; the electronic device obtains translation content corresponding to the source text content displayed on the first picture; and the electronic device automatically displays a second user interface, where a part or all of the translation content is displayed in the second user interface.

A machine translation method includes: an electronic device displays a first user interface, where source text content is displayed in the first user interface; after detecting an operation of triggering scrolling screenshot taking by a user, the electronic device automatically starts to take a scrolling screenshot; the electronic device obtains a first picture through scrolling screenshot taking; the electronic device obtains translation content corresponding to the source text content displayed on the first picture; and the electronic device automatically displays a second user interface, where a part or all of the translation content is displayed in the second user interface.

Provided are methods, systems, and devices for generating semantic objects and an output based on the detection or recognition of the state of an environment that includes objects. State data, based in part on sensor output, can be received from one or more sensors that detect a state of an environment including objects. Based in part on the state data, semantic objects are generated. The semantic objects can correspond to the objects and include a set of attributes. Based in part on the set of attributes of the semantic objects, one or more operating modes, associated with the semantic objects can be determined. Based in part on the one or more operating modes, object outputs associated with the semantic objects can be generated. The object outputs can include one or more visual indications or one or more audio indications.

Provided are methods, systems, and devices for generating semantic objects and an output based on the detection or recognition of the state of an environment that includes objects. State data, based in part on sensor output, can be received from one or more sensors that detect a state of an environment including objects. Based in part on the state data, semantic objects are generated. The semantic objects can correspond to the objects and include a set of attributes. Based in part on the set of attributes of the semantic objects, one or more operating modes, associated with the semantic objects can be determined. Based in part on the one or more operating modes, object outputs associated with the semantic objects can be generated. The object outputs can include one or more visual indications or one or more audio indications.

Methods and apparatus directed to utilizing an automated messaging system to initiate and/or adapt a dialog with at least one user, where the dialog occurs via user interface input and output devices of at least one computing device of the user. In some of those implementations, the automated messaging system identifies at least one task associated with the user and initiates the dialog with the user based on identifying the task. The automated messaging system may initiate the dialog to provide the user with additional information related to the task and/or to determine, based on user input provided during the dialog, values for one or more parameters of the task. In some implementations, the automated messaging system may further initiate performance of the task utilizing parameters determined during the dialog.

Methods and apparatus directed to utilizing an automated messaging system to initiate and/or adapt a dialog with at least one user, where the dialog occurs via user interface input and output devices of at least one computing device of the user. In some of those implementations, the automated messaging system identifies at least one task associated with the user and initiates the dialog with the user based on identifying the task. The automated messaging system may initiate the dialog to provide the user with additional information related to the task and/or to determine, based on user input provided during the dialog, values for one or more parameters of the task. In some implementations, the automated messaging system may further initiate performance of the task utilizing parameters determined during the dialog.

Provided are a speech translation method and apparatus, an electronic device and a storage medium. The method includes: acquiring a source speech corresponding to a to-be-translated language; acquiring a specified target language; inputting the source speech and indication information matched with the target language into a pre-trained speech translation model, where the speech translation model is configured to translate a language in a first language set into a language in a second language set, the first language set includes a plurality of languages, the first language set includes the to-be-translated language, the second language set includes a plurality of languages, and the second language set includes the target language; and acquiring a translated speech corresponding to the target language and output by the speech translation model; where the to-be-translated language is different from the target language.

A method and machine translation system for bi-directional translation of textual sequences between a first language and a second language are described. The machine translation system includes a first autoencoder configured to receive a vector representation of a first textual sequence in the first language and encode the vector representation of the first textual sequence into a first sentence embedding. The machine translation system also includes a sum-product network (SPN) configured to receive the first sentence embedding and generate a second sentence embedding by maximizing a first conditional probability of the second sentence embedding given the first sentence embedding and a second autoencoder receiving the second sentence embedding, the second autoencoder being trained to decode the second sentence embedding into a vector representation of a second textual sequence in the second language.