A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

A voice command-driven system and computer-implemented method are disclosed for selecting a data item in a list of text-based data items stored in a database using a simple affirmative voice command input without utilizing a connection to a network. The text-based data items in the list are converted to speech using an embedded text-to-speech engine and an audio output of a first converted data item is provided. A listening state is entered into for a predefined pause time to await receipt of the simple affirmative voice command input. If the simple affirmative voice command input is received during the predefined pause time, the first converted data item is selected for processing. If the simple affirmative voice command input is not received during the predefined pause time, an audio output of a next converted data item in the list is provided.

Features are disclosed for detecting words in audio using contextual information in addition to automatic speech recognition results. A detection model can be generated and used to determine whether a particular word, such as a keyword or “wake word,” has been uttered. The detection model can operate on features derived from an audio signal, contextual information associated with generation of the audio signal, and the like. In some embodiments, the detection model can be customized for particular users or groups of users based usage patterns associated with the users.

A speech recognition server has a speech recognition engine, and a mode control table to hold a speech recognition mode for each call. The speech recognition engine has a mode management unit to designate a speech recognition mode for a decoder, and an output analysis unit to analyze recognition result data speech-to-text converted by speech recognition. The output analysis unit designates the speech recognition mode for the mode management unit in accordance with result of analysis of the recognition result data speech-to-text converted by the speech recognition. The mode management unit designates the speech recognition mode for the decoder in accordance with the designation with the output analysis unit. Upon speech recognition of call data, it is possible to suppress hardware resource consumption while improve users' satisfaction.

A speech recognition server has a speech recognition engine, and a mode control table to hold a speech recognition mode for each call. The speech recognition engine has a mode management unit to designate a speech recognition mode for a decoder, and an output analysis unit to analyze recognition result data speech-to-text converted by speech recognition. The output analysis unit designates the speech recognition mode for the mode management unit in accordance with result of analysis of the recognition result data speech-to-text converted by the speech recognition. The mode management unit designates the speech recognition mode for the decoder in accordance with the designation with the output analysis unit. Upon speech recognition of call data, it is possible to suppress hardware resource consumption while improve users' satisfaction.

Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

The disclosed technology provides computer-to-wireless-voice integration methods and systems. In some implementations, the methods and systems deliver real-time voice instructions to users of required time-sensitive actions and ensure that such directives are received and a recipient effectively acts on the directives. The systems and methods include receiving a notification of an event from a terminal in a wireless active voice engine (WAVE) system, determining an active voice directive corresponding to the event with a WAVE module, converting the active voice directive into a voice event via a directive converter, and notifying a targeted recipient of the active voice directive corresponding to the event with a communications module. In some implementations, the systems and methods include sending a confirmation event via the receiver to the communications module that the active voice directive was received by the targeted recipient and communicating the active voice directive has been completed.

The disclosed technology provides computer-to-wireless-voice integration methods and systems. In some implementations, the methods and systems deliver real-time voice instructions to users of required time-sensitive actions and ensure that such directives are received and a recipient effectively acts on the directives. The systems and methods include receiving a notification of an event from a terminal in a wireless active voice engine (WAVE) system, determining an active voice directive corresponding to the event with a WAVE module, converting the active voice directive into a voice event via a directive converter, and notifying a targeted recipient of the active voice directive corresponding to the event with a communications module. In some implementations, the systems and methods include sending a confirmation event via the receiver to the communications module that the active voice directive was received by the targeted recipient and communicating the active voice directive has been completed.