US-20260128044-A1 - TRANSCRIPTION SYSTEM AND METHOD

US20260128044A1US 20260128044 A1US20260128044 A1US 20260128044A1US-20260128044-A1

Abstract

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server. Other embodiments are disclosed herein.

Inventors

Gavriil Papadopoulos
Zisis Tsiatsikas

Assignees

MITEL NETWORKS CORPORATION

Dates

Publication Date: 20260507
Application Date: 20241104

Claims (20)

1 . A system comprising: one or more processors; and one or more non-transitory memories storing computing instructions configured to communicate with the one or more processors and cause the one or more processors to perform: receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server.
2 . The system of claim 1 , wherein the computing instructions are further configured to cause the one or more processors to perform: prior to receiving the one or more electronic signals, analyzing a calendar invite scheduling the meeting; and pre-loading one or more predictive software applications onto a mobile device.
3 . The system of claim 2 , wherein: the analyzing the calendar invite comprises analyzing a specialty of the at least one of the two or more individuals; and the one or more predictive software applications comprise one or more specialized transcription software applications.
4 . The system of claim 2 , wherein the one or more predictive software applications comprise a predictive software application trained on training data encoding a specialty of the at least one of the two or more individuals.
5 . The system of claim 1 , wherein the analyzing the one or more electronic signals comprises analyzing one or more of voice tonality, background noises, gyroscope data, or open software applications to determine the privacy level.
6 . The system of claim 5 , wherein: the analyzing the one or more electronic signals comprises analyzing a voice tonality to determine whether the at least one of the two or more individuals is whispering; and the computing instructions are further configured to cause the one or more processors to perform: determining that the privacy level is above the predetermined threshold.
7 . The system of claim 1 , wherein the computing instructions are further configured to cause the one or more processors to perform: after transcribing the meeting, distributing an output of the one or more predictive software applications to each mobile electronic device of the two or more individuals.
8 . A method comprising: receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server.
9 . The method of claim 8 further comprising: prior to receiving the one or more electronic signals, analyzing a calendar invite scheduling the meeting; and pre-loading one or more predictive software applications onto a mobile device.
10 . The method of claim 9 , wherein: the analyzing the calendar invite comprises analyzing a specialty of the at least one of the two or more individuals; and the one or more predictive software applications comprise one or more specialized transcription software applications.
11 . The method of claim 10 , wherein the one or more predictive software applications comprise a predictive software application trained on training data encoding the specialty of the at least one of the two or more individuals.
12 . The method of claim 8 , wherein the analyzing the one or more electronic signals comprises analyzing one or more of voice tonality, background noises, gyroscope data, or open software applications to determine the privacy level.
13 . The method of claim 12 , wherein: the analyzing the one or more electronic signals comprises analyzing a voice tonality to determine whether the at least one of the two or more individuals is whispering; and the method further comprises: determining that the privacy level is above the predetermined threshold.
14 . The method of claim 8 further comprising: after transcribing the meeting, distributing an output of the one or more predictive software applications to each mobile electronic device of the two or more individuals.
15 . One or more articles of manufacture including one or more non-transitory, tangible computer readable storage mediums having instructions stored thereon that, in response to execution by one or more processors, cause the one or more processors to perform: receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server.
16 . The one or more articles of manufacture of claim 15 , wherein the instructions further cause the one or more processors to perform: prior to receiving the one or more electronic signals, analyzing a calendar invite scheduling the meeting; and pre-loading one or more predictive software applications onto a mobile device.
17 . The one or more articles of manufacture of claim 16 , wherein: the analyzing the calendar invite comprises analyzing a specialty of the at least one of the two or more individuals; and the one or more predictive software applications comprise one or more specialized transcription software applications.
18 . The one or more articles of manufacture of claim 16 , wherein the one or more predictive software applications comprise a predictive software application trained on training data encoding a specialty of the at least one of the two or more individuals.
19 . The one or more articles of manufacture of claim 15 , wherein the analyzing the one or more electronic signals comprises analyzing one or more of voice tonality, background noises, gyroscope data, or open software applications to determine the privacy level.
20 . The one or more articles of manufacture of claim 19 , wherein: the analyzing the one or more electronic signals comprises analyzing a voice tonality to determine whether the at least one of the two or more individuals is whispering; and the instructions further cause the one or more processors to perform: determining that the privacy level is above the predetermined threshold.

Description

TECHNICAL FIELD This disclosure relates generally to electronic communication methods, systems, and devices, and more specifically relates to electronic communication methods, systems, and devices, that employ context specific invocation of predictive models and context specific storage of their outputs. BACKGROUND In recent years, as the volume of digital data has grown, so too has the need for robust methods of protecting sensitive information. Personal data, such as financial records, medical histories, and other personally identifiable information (PII), is increasingly stored and processed on various digital platforms (e.g., locally and/or on remote servers). Further, many professions (e.g., legal, engineering, medical etc.) often handle and record confidential information on their electronic devices. While these digital systems offer significant benefits in terms of accessibility and scalability, they also introduce substantial risks associated with unauthorized access, data breaches, and compliance challenges with regulatory standards for data privacy. Further, for many professions, unauthorized access to sensitive data can lead to for harsh professional and legal consequences. These problems have been exacerbated by the rise of predictive software applications. For example, due to the black box nature of many of these software applications, it can be unclear where inputs and/or outputs of a predictive software application is stored and how they are used once they are stored. Therefore, in view of the above, there is a need for a novel system and method for invoking predictive software applications and storing their inputs and outputs. BRIEF DESCRIPTION OF THE DRAWINGS To facilitate further description of the embodiments, the following drawings are provided in which: FIG. 1 illustrates a flowchart for a method, according to an embodiment; FIG. 2 illustrates a representative block diagram of a computer network, according to an embodiment; and FIG. 3 illustrates a representative block diagram of a computer system, according to an embodiment. DESCRIPTION OF EXAMPLES OF EMBODIMENTS A number of embodiments can include a system. The system can include one or more processors and one or more non-transitory computer-readable storage devices. The one or more non-transitory computer-readable storage devices can store computing instructions. The computing instructions can be configured to communicate with the one or more processors and cause the one or more processors to perform receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server. Various embodiments include a method. The method can comprise receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server. Various embodiments can include an article of manufacture. The article of manufacture can include a non-transitory, tangible computer readable storage medium. The non-transitory, tangible computer readable storage medium can store instructions that, in response to execution by a computer, cause the computer to perform operations comprising receiving one or more electronic signals recording a meeting between two or more individuals; analyzing the one or more electronic signals to determine a privacy level of the meeting; when the privacy level is above a predetermined threshold, initializing a predictive software application locally on a mobile electronic device of at least one of the two or more individuals; and when the privacy level is below the predetermined threshold, initializing the predictive software application remotely on a cloud server. In many embodiments, the techniques described herein can provide a practical application and several technological improvements. In some embodiments, the techniques described herein can provide for improved data security. These techniques described herein can provide a significant improvement over conventional approaches of maintain data used or generated by predictive software applications, such as treating predictive software applications like black box. In many embodiments, the techniques described herein can benef