US-20260129042-A1 - METHOD AND SYSTEM FOR AUTHENTICATING USER USING ML DICTATION SUPPORT

US20260129042A1US 20260129042 A1US20260129042 A1US 20260129042A1US-20260129042-A1

Abstract

What is claimed is a system and method of authenticating a user to a service on a computing system, including obtaining, from the user, a spoken audio input signal relating to at least one authentication credential for the service, determining from the spoken audio input signal the at least one authentication credential, using at least one language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal; and triggering at least one authentication attempt to the service using the determined at least one authentication credential.

Inventors

Michael Marelus
Meier Marelus
Levi Marelus
Myriam Harroch
Gila Chacham

Assignees

FRIENDLYBUZZ COMPANY, PBC

Dates

Publication Date: 20260507
Application Date: 20241104

Claims (11)

1 . A method of authenticating a user to a service; the method comprising, on a computing system: obtaining, from the user, a spoken audio input signal relating to at least one authentication credential for the service; determining from the spoken audio input signal the at least one authentication credential, using at least one language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal; and triggering at least one authentication attempt to the service using the determined at least one authentication credential.
2 . The method of claim 1 , wherein the service is any one or more selected from the following: a wireless local area network; a virtual private network; and a digital account, such as a personal computer account or a social media account, an email account, a banking account, etc.
3 . The method of claim 1 , wherein the language-based ML model is a large language model, LLM, or is based on a LLM.
4 . The method of claim 1 , wherein said step of determining comprises: providing said at least one authentication credential, in the form of an audio input signal and/or in the form of a text input signal, to the at least one language-based ML model and prompting the at least one language-based ML model to obtain at least one variant representation of said at least one authentication credential; wherein the at least one language-based ML model is configured to take as input an initial representation, and to output one or more variant representations comprising one or more probable corrections to the initial representation.
5 . The method of claim 1 , comprising operating the at least one ML model to process some or all spoken audio input signal as a dictated input.
6 . A method of authenticating a user to a wireless local area network, WLAN, the method comprising, on a computing system: obtaining, from the user, a spoken audio input signal relating to at least one of: an identifier, ID, for the WLAN, and a password for the WLAN; determining from the spoken audio input signal the ID and/or the password, using a language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal; and triggering at least one authentication attempt to the WLAN using the determining ID and/or password.
7 . The method of claim 6 further comprising: obtaining, from the user, a second spoken audio input signal relating to a password for the WLAN; and determining from the second spoken audio input signal the password, using a language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal, before the step of triggering at least one authentication attempt to the WLAN using the determined ID and password.
8 . The method of claim 6 , further comprising: detecting an identifier, ID, for the WLAN by scanning a radio frequency range accessible to the computing system.
9 . The method of claim 8 , wherein said step of detecting the ID for the WLAN by scanning comprises: if no IDs are detected in said scanning, outputting a failure notification to the user, and re-attempting or halting the method; if one ID is detected in said scanning, setting said one ID as the ID of the WLAN to be authenticated to; or if multiple IDs are detected in said scanning, either: transparently to the user, and optionally in an iterative manner, selecting at least one ID from the multiple detected IDs as the ID of the WLAN to be authenticated to, by making use of a pre-defined heuristic, preferably based on ranking respective Relative Signal Strength Identifier, RSSI, values of the multiple detected IDs; or outputting to the user at least one ID of the multiple IDs; receiving from the user selection data designating an ID of the at least one output ID; and selecting the designated ID as the ID of the WLAN to be authenticated to.
10 . The method of claim 9 , wherein the at least one ID of the multiple IDs is output to the user via a visual display or an audio speaker or a combination thereof; and wherein the selection data from the user comprise a spoken audio selection input signal or a click or touch selection input signal.
11 . A computing system for authenticating a user to a service; the computing system comprising at least one processor and at least one memory the at least one memory storing computer-executable instructions configured for, when executed by the processor, causing the computing system to perform: obtaining, from the user, a spoken audio input signal relating to at least one authentication credential for the service; determining from the spoken audio input signal the at least one authentication credential, using at least one language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal; and triggering at least one authentication attempt to the service using the determined at least one authentication credential.

Description

TECHNICAL FIELD The present disclosure generally relates to user authentication to a service. Particular embodiments relate to a method of authenticating a user to a service, and to a related computer program, non-transitory computer-readable storage medium, and computing system. BACKGROUND In certain situations, a user may desire to access a service, e.g. a WLAN in a home setting. To do so, the user needs to supply or prove certain authentication credentials. In some cases, the user additionally needs to know further specific information, e.g. which WLAN is to be used, and where and how to supply the authentication credentials in order to authenticate themselves to the WLAN. Conventionally, the user needs to manually enter the authentication credentials into an authentication interface, which is typically but not always a visual interface. The visual interface that the user can use may typically be provided by a computing system such as the user's personal computer, PC, or smart device, e.g. a smartphone, and the operation of entering is generally conducted through a touchscreen or keyboard and the output (e.g. prompt to input password; success message; etc.) is generally output on the visual interface too. The operation of entering the authentication credentials requires that the user takes great care to type the relevant data, in string format, into the visual interface. This is especially the case for passwords, but also for other kinds of authentication credentials. SUMMARY Given that there is a desire for security, in particular if the authentication credentials comprise a password or passkey or passphrase, the string to be typed by the user is typically a long (e.g. 8 or more characters or even 14 or more characters), complicated (and ideally even random) string of characters, optionally including various non-alphanumeric symbols. This means that the user may find typing the string, for example by way of a touch screen or a keyboard, burdensome. Moreover, the user may make human mistakes when typing the string, for instance due to the length and/or the complexity of the string, which increases the overall time and effort required to authenticate to the service. These concerns don't apply for passwords only, as similar concerns may apply to other types of authentication credentials, e.g. the WLAN's identifier, including for example where (especially in urban settings) there may be many locally co-existing WLANs, and these may be distinguished only by a difference that is relatively subtle for the average user (e.g. “dlink-AB12-2.4 GHz”, “dlink-AB21-2.4 GHz”, and “dlink-AB12-5 GHz”). Moreover, in order for a user to select, for example, a WLAN and/or type a password, for example, the computing system needs to include a keyboard and/or a touchscreen and a related graphical user interface, and related driver software. It is an aim of at least some embodiments of the present disclosure to address the shortcomings described herein. Accordingly, the present disclosure provides embodiments according to the included claims. The embodiments described herein are provided for illustrative purposes and should not be construed as limiting the scope of the invention. It is to be understood that the invention encompasses other embodiments and variations that are within the scope of the appended claims. The invention is not restricted to the specific configurations, arrangements, and features described herein. The invention has wide applicability and should not be limited to the specific examples provided. The embodiments disclosed are merely exemplary, and the skilled person will appreciate that various modifications and alternative designs can be made without departing from the scope of the invention. BRIEF DESCRIPTION OF THE DRAWINGS In the following description, a number of exemplary embodiments will be described in more detail, to further help understanding, with reference to the appended drawings, in which: FIG. 1 schematically illustrates a flowchart of an exemplary embodiment of a method 100 according to the present disclosure; FIG. 2 schematically illustrates a system diagram of an exemplary embodiment of a computing system 1000 according to the present disclosure; and FIG. 3 schematically illustrates a system diagram of an exemplary embodiment of a computing system 1100 according to the present disclosure. DETAILED DESCRIPTION In particular, in a first aspect of the present disclosure, there is provided a method of authenticating a user to a service; the method comprising, on a computing system: obtaining, from the user, a spoken audio input signal relating to at least one authentication credential for the service;determining from the spoken audio input signal the at least one authentication credential, using at least one language-based machine learning, ML, model trained for analyzing an input signal pertaining to the spoken audio input signal; andtriggering at least one authentication attempt to the servi