Abstract: An intelligent noise cancellation process for audio or video conference calls. Different levels of deep learning model classifiers are leveraged to determine, in real-time, the presence of noise data and voice data in audio input signals being received at numerous audio input devices. In response, appropriate action is taken to prevent the noise data from being included in the subsequent audio communication. Specifically, a lightweight neural network-based model classifier is initially used to identify noise data and/or the presence of predetermined trigger words or phrases in audio input signals. In the event that the lightweight model is unable to identify the presence of the triggering words/phrases, a heavyweight neural network-based model classifier is called upon, whereby the audio signals are attempted to be converted to a human-understandable language format (i.e., a text format) as a means of positively identifying voice data in audio input signals.

Abstract: An intelligent noise cancellation process for audio or video conference calls. Different levels of deep learning model classifiers are leveraged to determine, in real-time, the presence of noise data and voice data in audio input signals being received at numerous audio input devices. In response, appropriate action is taken to prevent the noise data from being included in the subsequent audio communication. Specifically, a lightweight neural network-based model classifier is initially used to identify noise data and/or the presence of predetermined trigger words or phrases in audio input signals. In the event that the lightweight model is unable to identify the presence of the triggering words/phrases, a heavyweight neural network-based model classifier is called upon, whereby the audio signals are attempted to be converted to a human-understandable language format (i.e., a text format) as a means of positively identifying voice data in audio input signals.

Abstract: A mechanism for consolidating communications between a computer tenant and a web services layer is provided. The mechanism may include a web services layer. The web services layer may be configured to receive communications, via an authentication validation module, from an authentication service. The authentication service may be in communication with the computer tenant and/or the web services layer. The web services layer may be configured to receive authorization data, via an authorization module, from an authorization data store. The web services layer may also receive and transmit logged calls from a log database. The logged calls may store calls from the computer tenant to the web services layer and calls from the web services layer to the authentication server. The computer tenant may initiate communication with the web services layer. Included in the communications may be a token.

Abstract: A mechanism for consolidating communications between a computer tenant and a web services layer is provided. The mechanism may include a web services layer. The web services layer may be configured to receive communications, via an authentication validation module, from an authentication service. The authentication service may be in communication with the computer tenant and/or the web services layer. The web services layer may be configured to receive authorization data, via an authorization module, from an authorization data store. The web services layer may also receive and transmit logged calls from a log database. The logged calls may store calls from the computer tenant to the web services layer and calls from the web services layer to the authentication server. The computer tenant may initiate communication with the web services layer. Included in the communications may be a token.