Abstract:
Systems and methods are provided for associating a phonetic pronunciation with a name by receiving the name, mapping the name to a plurality of monosyllabic components that are combinable to construct the phonetic pronunciation of the name, receiving a user input to select one or more of the plurality, and combining the selected one or more of the plurality of monosyllabic components to construct the phonetic pronunciation of the name.
Abstract:
While an electronic device with a display and a touch-sensitive surface is in a screen reader accessibility mode, the device displays a character input area and a keyboard, the keyboard including a plurality of key icons. The device detects a sequence of one or more gestures on the touch-sensitive surface that correspond to one or more characters. A respective gesture of the one or more gestures that corresponds to a respective character is a single finger gesture that moves across the touch-sensitive surface along a respective path that corresponds to the respective character. The respective path traverses one or more locations on the touch-sensitive surface that correspond to one or more key icons of the plurality of key icons without activating the one or more key icons. In response to detecting the respective gesture, the device enters the corresponding respective character in the character input area of the display.
Abstract:
Systems and processes for robust end-pointing of speech signals using speaker recognition are provided. In one example process, a stream of audio having a spoken user request can be received. A first likelihood that the stream of audio includes user speech can be determined. A second likelihood that the stream of audio includes user speech spoken by an authorized user can be determined. A start-point or an end-point of the spoken user request can be determined based at least in part on the first likelihood and the second likelihood.
Abstract:
Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.
Abstract:
Techniques for providing reminders based on social interactions between users of electronic devices are described. Social reminders can be set to trigger based on social interactions of users. For example, a user may request to be reminded to discuss a certain discussion topic with a particular phonebook contact, when the user next encounters the contact.
Abstract:
A speech recognition system uses, in one embodiment, an extended phonetic dictionary that is obtained by processing words in a user's set of databases, such as a user's contacts database, with a set of pronunciation guessers. The speech recognition system can use a conventional phonetic dictionary and the extended phonetic dictionary to recognize speech inputs that are user requests to use the contacts database, for example, to make a phone call, etc. The extended phonetic dictionary can be updated in response to changes in the contacts database, and the set of pronunciation guessers can include pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser.
Abstract:
Techniques for providing reminders based on social interactions between users of electronic devices are described. Social reminders can be set to trigger based on social interactions of users. For example, a user may request to be reminded to discuss a certain discussion topic with a particular phonebook contact, when the user next encounters the contact.
Abstract:
Systems and processes for generating a shared pronunciation lexicon and using the shared pronunciation lexicon to interpret spoken user inputs received by a virtual assistant are provided. In one example, the process can include receiving pronunciations for words or named entities from multiple users. The pronunciations can be tagged with context tags and stored in the shared pronunciation lexicon. The shared pronunciation lexicon can then be used to interpret a spoken user input received by a user device by determining a relevant subset of the shared pronunciation lexicon based on contextual information associated with the user device and performing speech-to-text conversion on the spoken user input using the determined subset of the shared pronunciation lexicon.
Abstract:
Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.