Mark LaBosco

Bio: Mark LaBosco is an academic researcher. The author has contributed to research in topics: Controller (computing). The author has an hindex of 2, co-authored 2 publications receiving 41 citations.

Acoustic sensory network

Abstract: A system is provided for determining which controllable device an audible command is directed towards. The system comprises two or more controllable devices, two or more electronic devices, each of which is adapted to receive the audible command, add a respective electronic device identifier to the received audible command, time and date stamp the received audible command, and transmit the respective time and date stamped versions of the audible command, and wherein each of the two or more electronic device are further adapted to controller respective ones of the two or more controllable devices, and a central processor adapted to receive each of the transmitted time and date stamped versions of the audible command and perform processing based on the time and date stamp, wherein the electronic device that reports the earlier time and date stamp, as ascertained by the respective electronic device identifier and a comparison of each of the time and date stamps performed by the central processor, is the electronic device to which the audible command is directed towards.

System and method for determining recipient of spoken command in a control system

Abstract: Disclosed is an apparatus and method for determining which controllable device an audible command is directed towards, the method comprising: receiving at each of two or more controlling devices the audible command signal, the audible command being directed to control at least one of two or more controllable devices controlled by a respective one of the two or more controlling devices; digitizing each of the received audible command signals; attaching a unique identifier to each digitized audible command so as to uniquely correlate it to a respective controlling device; determining a magnitude of each of the digitized audible command; determining a digitized audible command with the greatest magnitude, and further determining to which controlling device the audible command is directed to on the basis of the unique identifier associated with the digitized audible command with the greatest magnitude; performing speech recognition on the digitized audible command with the greatest magnitude; and forwarding a command to the controlling device corresponding to the digitized audible command with the greatest magnitude, the command corresponding to the audible command that can be implemented on the controllable device controlled by the controlling device.

Multi-command single utterance input method

Abstract: 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.

User profiling for voice input processing

Abstract: 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.

Intelligent assistant for home automation

Abstract: 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.

Speaker identification and unsupervised speaker adaptation techniques

Abstract: 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.

Competing devices responding to voice triggers

Abstract: At a first electronic device with a display and a microphone: sampling audio input using the first microphone; in accordance with the sampling of audio input using the first microphone, sending stop instructions to a second electronic device with a second microphone, the second electronic device external to the first electronic device, wherein the second electronic device is configured to respond to audio input received using the second microphone, and wherein the stop instructions instruct the second electronic device to forgo responding to audio input received using the second microphone, wherein responding to audio input received using the second microphone comprises providing perceptible output.