Abstract:
Computer implemented techniques for performing transliteration of input text in a first character set to a second character set are disclosed. The techniques include receiving input text and determining a set of possible transliterations of the input text based on a plurality of mapping standards. Each mapping standard defines a mapping of characters in the first character set to characters in the second character set. The techniques further include determining a set of candidate words in the target language based on the possible transliterations and a text corpus. The techniques also include determining a likelihood score for each one of the candidate words based on a language model in the target language previously received words. The techniques also include providing one or more candidate words based on the likelihood scores and receiving a user selection indicating one of the candidate words.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium and a method for automatically providing support solutions in response to user feedback items. The method comprises receiving user feedback items and corresponding support solutions. The method further comprises identifying, using clustering techniques, associations between the user feedback items and the corresponding support solutions. The method further comprises storing the identified associations as an items-solutions model that correlates the user feedback items with the corresponding support solutions. The method further comprises receiving a new user feedback item. The method further comprises automatically determining, using the items-solutions model, at least one support solution that corresponds to the new user feedback item. The method further comprises providing the at least one support solution in response to the received new user feedback item.
Abstract:
The disclosed subject matter provides a system, computer readable storage medium, and a method providing an audio and textual transcript of a communication. A conferencing services may receive audio or audio visual signals from a plurality of different devices that receive voice communications from participants in a communication, such as a chat or teleconference. The audio signals representing voice (speech) communications input into respective different devices by the participants. A translation services server may receive over a separate communication channel the audio signals for translation into a second language. As managed by the translation services server, the audio signals may be converted into textual data. The textual data may be translated into text of different languages based the language preferences of the end user devices in the teleconference. The translated text may be further translated into audio signals.
Abstract:
Information about named entities referenced in an electronic book (ebook) is provided to a client device. An ebook identifier identifying the ebook is received from the client device. A set of layers available for use with the ebook is determined. The layers in the set provide information associated with the ebook and a layer in the set provides information associated with named entities referenced in content of the ebook. A content range identifying a range of content of the ebook for which layer information is requested and an identification of one or more of the layers in the set for which layer information is requested is received from the client device. Layer information associated with the ebook content identified by the content range for the identified layers is transmitted to the client device. The transmitted layer information includes information associated with named entities referenced by ebook content.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium and a method for automatically providing support solutions in response to user feedback items. The method comprises receiving user feedback items and corresponding support solutions. The method further comprises identifying, using clustering techniques, associations between the user feedback items and the corresponding support solutions. The method further comprises storing the identified associations as an items-solutions model that correlates the user feedback items with the corresponding support solutions. The method further comprises receiving a new user feedback item. The method further comprises automatically determining, using the items-solutions model, at least one support solution that corresponds to the new user feedback item. The method further comprises providing the at least one support solution in response to the received new user feedback item.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium and a method for automatically providing support solutions in response to user feedback items. The method comprises receiving user feedback items and corresponding support solutions. The method further comprises identifying, using clustering techniques, associations between the user feedback items and the corresponding support solutions. The method further comprises storing the identified associations as an items-solutions model that correlates the user feedback items with the corresponding support solutions. The method further comprises receiving a new user feedback item. The method further comprises automatically determining, using the items-solutions model, at least one support solution that corresponds to the new user feedback item. The method further comprises providing the at least one support solution in response to the received new user feedback item.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium and a method for automatically providing support solutions in response to user feedback items. The method comprises receiving user feedback items and corresponding support solutions. The method further comprises identifying, using clustering techniques, associations between the user feedback items and the corresponding support solutions. The method further comprises storing the identified associations as an items-solutions model that correlates the user feedback items with the corresponding support solutions. The method further comprises receiving a new user feedback item. The method further comprises automatically determining, using the items-solutions model, at least one support solution that corresponds to the new user feedback item. The method further comprises providing the at least one support solution in response to the received new user feedback item.
Abstract:
A computer-implemented method for generating a machine-learning model can include receiving, at a computing device having one or more processors, a plurality of reported phone numbers from telephone users, a plurality of posted phone numbers from one or more websites, and transcriptions of messages associated with a plurality of calling phone numbers. The machine-learning model is generated based on these various inputs and stored at the computing device. The model is configured to determine a probability that an unknown phone message is unwanted based on a phone number from which the unknown phone message originated.