A system and method are disclosed for training a machine-learning model to detect characteristics of fraudulent calls. The machine-learning model is trained using audio clips, voice recognition, call handler feedback and general public knowledge of commercial risks to detect and divert fraudulent calls, thereby alleviating the burdens otherwise placed on call center service representatives.

Certain aspects of the disclosure are directed to monitoring user-data communications corresponding to a user-generated message. According to a specific example, user-data communications, which are addressed to a client among a plurality of remotely-situated client entities, are directed to a message recording system. Each of the plurality of remotely-situated client entities are respectively configured and arranged to interface with a data communications server providing data communications services on a subscription basis. During recording of a message associated with the user-data communications and on the message recording system, speech characteristic parameters of the message may be analyzed, and a sentiment score and a criticality score for the message, may be determined. During the recording of the message, the user-data communications may be routed based on the determined sentiment score and criticality score.

A method may include obtaining first audio data originating at a first device during a communication session between the first device and a second device. The method may also include obtaining a first text string that is a transcription of the first audio data, where the first text string may be generated using automatic speech recognition technology using the first audio data. The method may also include obtaining a second text string that is a transcription of second audio data, where the second audio data may include a revoicing of the first audio data by a captioning assistant and the second text string may be generated by the automatic speech recognition technology using the second audio data. The method may further include generating an output text string from the first text string and the second text string and using the output text string as a transcription of the speech.

The present invention relates to a system for retrieving information from a network such as the Internet. A user creates a user-defined record in a database that identifies an information source, such as a web site, containing information of interest to the user. This record identifies the location of the information source and also contains a recognition grammar based upon a speech command assigned by the user. Upon receiving the speech command from the user that is described within the recognition grammar, a network interface system accesses the information source and retrieves the information requested by the user.

A recording system has a listener processor for automatically capturing events involving computer applications during a dialogue involving the user of the computer. The system generates a visual transcript of events on a timeline. It automatically detects start of a dialogue and proceeds to detect events and determines if they are configured as transcript events, before detecting end of the dialogue. The system may associate dialogue events with audio clips, using meta tags.

Methods, computer program products, and systems are presented. The methods, computer program products, and systems can include, for instance: determining, in performance of an interactive voice response (IVR) session, prompting data for presenting to a user, and storing text based data defining the prompting data into a data repository; presenting the prompting data to the user; receiving return voice string data from the user in response to the prompting data; generating a plurality of candidate text strings associated to the return voice string of the user; examining the text based data defining the prompting data; augmenting the plurality of candidate text strings in dependence on a result of the examining to provide a plurality of augmented candidate text strings associated to the return voice string data; and evaluating respective ones of the plurality of augmented candidate text strings associated to the return voice string data; and selecting one of the augmented candidate text strings as a returned transcription associated to the return voice string data.

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.

Integration of VoIP phone services with Intelligent Cloud Voice Recognition for emergency services overcomes limitations of conventional residential telephone technology to inexpensively provide more useful and advanced residential telephone services. For example, in an embodiment, a communication method may comprise establishing a communications session between either a user device and a telephone system or between a user device and voice recognition system, if the communications session is between a user device and a telephone system, extending the communications session to include a voice recognition system, if the communications session is between a user device and a voice recognition system, extending the communications session to include a telephone system, providing voice or speech information to the voice recognition system from the user device, and performing at least one function with the voice recognition system based on the provided voice or speech information.

A relay for captioning a hearing user's (HU's) voice signal during a phone call between an HU and a hearing assisted user (AU), the HU using an HU device and the AU using an AU device where the HU voice signal is transmitted from the HU device to the AU device, the relay comprising a display screen, a processor linked to the display and programmed to perform the steps of receiving the HU voice signal from the AU device, transmitting the HU voice signal to a remote automatic speech recognition (ASR) server running ASR software that converts the HU voice signal to ASR generated text, the remote ASR server located at a remote location from the relay, receiving the ASR generated text from the ASR server, present the ASR generated text for viewing by a call assistant (CA) via the display and transmitting the ASR generated text to the AU device.

Methods, systems, and apparatus for an automated calling system are disclosed. Some implementations are directed to using a bot to initiate telephone calls and conduct telephone conversations with a user. The bot may be interrupted while providing synthesized speech during the telephone call. The interruption can be classified into one of multiple disparate interruption types, and the bot can react to the interruption based on the interruption type. Some implementations are directed to determining that a first user is placed on hold by a second user during a telephone conversation, and maintaining the telephone call in an active state in response to determining the first user hung up the telephone call. The first user can be notified when the second user rejoins the call, and a bot associated with the first user can notify the first user that the second user has rejoined the telephone call.