Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

A communication system can include terminal devices that communicate with a social network or a computer server device for scheduling use of conference resources and/or for using conference appliances that may be located in a conference room being used for a video conference or teleconference. The communication system can be configured to permit a user to use such resources without having to have a user's device be physically and directly connected by wiring to a conference appliance or communication device. The communication system can also be configured to validate participants to help ensure that only authorized personnel are properly attending a scheduled conference based on audio and/or video input received for the different participants and can also be configured to allow screen sharing to be performed during a video conference or teleconference.

Systems, methods performed by data processing apparatus and computer storage media encoded with computer programs for receiving an utterance from a user in a multi-user environment, each user having an associated set of available resources, determining that the received utterance includes at least one predetermined word, comparing speaker identification features of the uttered predetermined word with speaker identification features of each of a plurality of previous utterances of the predetermined word, the plurality of previous predetermined word utterances corresponding to different known users in the multi-user environment, attempting to identify the user associated with the uttered predetermined word as matching one of the known users in the multi-user environment, and based on a result of the attempt to identify, selectively providing the user with access to one or more resources associated with a corresponding known user.

Systems, methods performed by data processing apparatus and computer storage media encoded with computer programs for receiving an utterance from a user in a multi-user environment, each user having an associated set of available resources, determining that the received utterance includes at least one predetermined word, comparing speaker identification features of the uttered predetermined word with speaker identification features of each of a plurality of previous utterances of the predetermined word, the plurality of previous predetermined word utterances corresponding to different known users in the multi-user environment, attempting to identify the user associated with the uttered predetermined word as matching one of the known users in the multi-user environment, and based on a result of the attempt to identify, selectively providing the user with access to one or more resources associated with a corresponding known user.

A human-computer interaction method relates to the field of human-computer interaction technologies. The method includes: establishing a correspondence between a first voiceprint and a first output position on a touchscreen; and receiving first voice, and when it is determined that a voiceprint of the first voice matches the first voiceprint, recognizing content of the voice, and outputting and displaying the content to the first output position.

A human-computer interaction method relates to the field of human-computer interaction technologies. The method includes: establishing a correspondence between a first voiceprint and a first output position on a touchscreen; and receiving first voice, and when it is determined that a voiceprint of the first voice matches the first voiceprint, recognizing content of the voice, and outputting and displaying the content to the first output position.

Machine natural language processing to analyze language in apparatus, systems, and methods of using are provided. Audio from camera footage can be transcribed in one exemplary method includes extracting at least one audio segment from a body camera video track, detecting voice activity to identify starting and ending timestamps of voice, transcribing the at least one audio segment to identify and separate audio of at least a first speaker, and scoring the audio of the first speaker to identify interactions of interest. Audio could be analyzed and scored to record verbal performance, respectfulness, wellness, etc. and speakers from the audio can be detected.

Machine natural language processing to analyze language in apparatus, systems, and methods of using are provided. Audio from camera footage can be transcribed in one exemplary method includes extracting at least one audio segment from a body camera video track, detecting voice activity to identify starting and ending timestamps of voice, transcribing the at least one audio segment to identify and separate audio of at least a first speaker, and scoring the audio of the first speaker to identify interactions of interest. Audio could be analyzed and scored to record verbal performance, respectfulness, wellness, etc. and speakers from the audio can be detected.

The present invention discloses a method of noise reduction for an intelligent network communication, which includes the following steps: first, receiving a local sound message through a sound receiver of a communication device at the transmitting end. Next, a voice recognizer is used to identify the voice characteristics of the speaker; then, it is determined from a voice database whether there is a corresponding or similar voice characteristic of the speaker recognized by the voice recognizer. Finally, filtering other signals other than the voice characteristic signal of the speaker through a sound filter to obtain the original sound emitted by the speaker.

An automated speech recognition (“ASR”) system with an audio processing engine and contextual transcription engine on a computing device is provided. The audio processing engine determines audio segmentation corresponding with multiple identified speakers of audio data. The contextual transcription engine generates a text file based on the audio data in a legally-formatted transcript using one or more AI/ML models. Embodiments of the ASR system provide provides results that will comply with most of the stenographic standards for legal transcription out of the box without further setup or tuning.