Abstract:
In one example, a method includes receiving, by a first computing device and from a second computing device, an image comprising an object. A user may be associated with a social networking service and the second computing device. The method further includes selecting a social group associated with the user in the social networking service. The selection may be based at least in part on one or more characteristics associated with the object. The method also includes sending, by the first computing device to the second computing device, an indication of the social group selected by the first computing device.
Abstract:
Systems and methods for using a digital image in a social networking system may use digital image to identify a physical entity. Information about the identified physical entity may be provided to an electronic display for review by a user. The user may perform a social networking action with the identified physical entity or a website associated with the physical entity. Social networking actions may include rating or commenting about the physical entity or the associated website via a social networking system. Social networking actions may also include sharing information about the physical entity or associated website with another user via the social networking system.
Abstract:
A set of benchmark text strings may be classified to provide a set of benchmark classifications. The benchmark text strings in the set may correspond to a benchmark corpus of benchmark utterances in a particular language. A benchmark classification distribution of the set of benchmark classifications may be determined. A respective classification for each text string in a corpus of text strings may also be determined. Text strings from the corpus of text strings may be sampled to form a training corpus of training text strings such that the classifications of the training text strings have a training text string classification distribution that is based on the benchmark classification distribution. The training corpus of training text strings may be used to train an automatic speech recognition (ASR) system.
Abstract:
A method, computer program product, and computing system for providing a plurality of users of a social network with the ability to indicate affinity with an electronic object. An indication is received from a first user of the plurality of users to initiate an object-specific, synchronous communication session concerning the electronic object. Electronic invitations to join the object-specific, synchronous communication session are provided to one or more invited users of the plurality of users of the social network. A request is received, from at least one of the invited users, to join the object-specific, synchronous communication session. The object-specific, synchronous communication session is provided for the first user and the at least one of the invited users.
Abstract:
A computer-implemented technique includes receiving, at a computing device including one or more processors, a touch input from a user. The touch input includes (i) a spot input indicating a request to provide a speech input to the computing device followed by (ii) a slide input indicating a desired language for automatic speech recognition of the speech input. The technique includes receiving, at the computing device, the speech input from the user. The technique includes obtaining, at the computing device, one or more recognized characters resulting from automatic speech recognition of the speech input using the desired language. The technique also includes outputting, at the computing device, the one or more recognized characters.