Systems and processes are disclosed for handling a multi-part voice command for a virtual assistant. Speech input can be received from a user that includes multiple actionable commands within a single utterance. A text string can be generated from the speech input using a speech transcription process. The text string can be parsed into multiple candidate substrings based on domain keywords, imperative verbs, predetermined substring lengths, or the like. For each candidate substring, a probability can be determined indicating whether the candidate substring corresponds to an actionable command. Such probabilities can be determined based on semantic coherence, similarity to user request templates, querying services to determine manageability, or the like. If the probabilities exceed a threshold, the user intent of each substring can be determined, processes associated with the user intents can be executed, and an acknowledgment can be provided to the user.

Multi-command single utterance input method

A mobile electronic device has a touch sensitive screen and an accelerometer. A translator is to translate a word or phrase that is in a first human language and that is entered via a first virtual keyboard displayed on the touch sensitive screen, into a second human language. A translator is to cause the touch sensitive screen to display the translated word or phrase and a second virtual keyboard having characters in the second human language, in response to the accelerometer detecting a change in the physical orientation of the device or movement of the device. Other embodiments are also described and claimed.

Mobile device having human language translation capability with positional feedback

This is directed to processing voice inputs received by an electronic device. In particular, this is directed to receiving a voice input and identifying the user providing the voice input. The voice input can be processed using a subset of words from a library used to identify the words or phrases of the voice input. The particular subset can be selected such that voice inputs provided by the user are more likely to include words from the subset. The subset of the library can be selected using any suitable approach, including for example based on the user's interests and words that relate to those interests. For example, the subset can include one or more words related to media items selected by the user for storage on the electronic device, names of the user's contacts, applications or processes used by the user, or any other words relating to the user's interactions with the device.

User profiling for voice input processing

This relates to systems and processes for using a virtual assistant to control electronic devices. In one example process, a user can speak an input in natural language form to a user device to control one or more electronic devices. The user device can transmit the user speech to a server to be converted into a textual representation. The server can identify the one or more electronic devices and appropriate commands to be performed by the one or more electronic devices based on the textual representation. The identified one or more devices and commands to be performed can be transmitted back to the user device, which can forward the commands to the appropriate one or more electronic devices for execution. In response to receiving the commands, the one or more electronic devices can perform the commands and transmit their current states to the user device.

Intelligent assistant for home automation

Systems and processes for generating a speaker profile for use in performing speaker identification for a virtual assistant are provided. One example process can include receiving an audio input including user speech and determining whether a speaker of the user speech is a predetermined user based on a speaker profile for the predetermined user. In response to determining that the speaker of the user speech is the predetermined user, the user speech can be added to the speaker profile and operation of the virtual assistant can be triggered. In response to determining that the speaker of the user speech is not the predetermined user, the user speech can be added to an alternate speaker profile and operation of the virtual assistant may not be triggered. In some examples, contextual information can be used to verify results produced by the speaker identification process.

Speaker identification and unsupervised speaker adaptation techniques

Chat-bots are computer programs coded to have a textual or verbal conversation which is logical or intelligent. Chat-bots are designed to make humans believe that they are talking to a human; but instead they are in fact talking to a machine. Taking advantage of this transparency property of chat-bot, an artificial character and personality can be given to a chat-bot which acts like a person of a specific profession. This paper describes an approach to the idea of implementing web-based artificially intelligent chat-bot as a personal assistant of the user, which stimulates setting and initiating meetings of user with his clients. The exchange of information happens through email conversations whereas its evaluation happens through natural language procession and natural language generation and AIML files. General Terms AIML, Artificial Intelligence, Pattern Matching.

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Namita Mhatre

Papers

Donna Interactive Chat-bot acting as a Personal Assistant