A computer system conducts a communication session using a communication agent. Organizational information relating to a user is received. A communication session is conducted between a user and a communication agent, wherein the communication agent discusses one or more topics of an organization of the user. Organizational analytics are generated by applying natural language processing to user feedback to identify user issues pertaining to the one or more organizational topics wherein the organizational analytics are based on user sentiment toward the one or more organizational topics. The organizational analytics are reported to a third party. Embodiments of the present invention further include a method and program product for conducting a communication session using a communication agent in substantially the same manner described above.

Disclosed herein are systems and methods for receiving a voice command and determining an appropriate action for the media playback system to execute based on user identification. The systems and methods receive a voice command for a media playback system, and determines whether the voice command was received from a registered user of the media playback system. In response to determining that the voice command was received from a registered user, the systems and methods configure an instruction for the media playback system based on content from the voice command and information in a user profile for the registered user.

Provided are a method, system, and computer program product in which a service orchestration layer is configured in a telecommunications network. Personalized pending user actions are transmitted to a user equipment, in response to a hold being performed over a first communications channel to the user equipment.

Disclosed is a voice interaction method and apparatus. In the above method, a first voice control instruction is acquired, and a first operation corresponding to the first voice control instruction is executed; mixed audio data are gathered, where the mixed audio data includes: audio data played when the first operation is executed and a second voice control instruction; the played audio data are filtered out from the mixed audio data, and the second voice control instruction is identified; and it is switched from the first operation to a second operation corresponding to the second voice control instruction according to the second voice control instruction.

Methods and systems for managing multiple tasks using a dialog are presented. In some embodiments, a processor may parse a first natural language user input received at a user device to extract task related information from the first natural language user input. In response to identifying that the first natural language user input comprises a request to perform a first task, the processor may initiate execution of the first task. The user device may receive a second natural language user input after execution of the first task has been initiated which requests execution of a second task. The processor may initiate execution of the second task before execution of the first task is complete.

Provided are embodiments for a computer-implemented method for interacting with a user by an automated response system supporting topic switching and information collection. The computer-implemented method includes receiving a plurality of utterances from the user by the automated response system, and analyzing the utterances to form a first topic thread and an information collection objective. The computer-implemented method also includes utilizing an information collection user interface to gather data to support the information collection objective, and providing responses to the user after the gathered data related to the first topic thread. Also provided are embodiments for a system and computer program product for implementing the techniques described herein.

A computer system comprises an input configured to receive voice input from a user, the voice input having speech intervals separated by non-speech intervals; an ASR system configured to identify individual words in the voice input during speech intervals thereof, and store the identified words in memory; a response generation module configured to generate based on the words stored in the memory an audio response for outputting to the user; and a response delivery module configured to begin outputting the audio response to the user during a non-speech interval of the voice input, wherein the outputting of the audio response is terminated before it has completed in response to a subsequent speech interval of the voice input commencing whilst the audio response is still being outputted.

Voice input is received from a user. An ASR system generates in memory a set of words it has identified in the voice input, and update the set each time it identifies a new word in the voice input to add the new word to the set, during at least one interval of speech activity. Information is pre-retrieved whilst the speech activity interval is still ongoing, for conveying in a response to be outputted at the end of the speech activity interval.

A computer system comprises an input configured to receive voice input from a user, the voice input having speech intervals separated by non-speech intervals; an ASR system configured to identify individual words in the voice input during speech intervals of the voice input, and store the identified words in memory; a speech overload detection module configured to detect at a time during a speech interval of the voice input a speech overload condition; and a notification module configured to output to the user, in response to said to detection, a notification of the speech overload condition.

Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, based on content of an existing human-to-computer dialog session between a user and an automated assistant, an entity mentioned by the user or automated assistant may be identified. Fact(s)s related to the entity or to another entity that is related to the entity may be identified based on entity data contained in database(s). For each of the fact(s), a corresponding measure of potential interest to the user may be determined. Unsolicited natural language content may then be generated that includes one or more of the facts selected based on the corresponding measure(s) of potential interest. The automated assistant may then incorporate the unsolicited content into the existing human-to-computer dialog session or a subsequent human-to-computer dialog session.