Patent ID: 12230260

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations in addition to the described example embodiments. Thus, the following more detailed description of the example embodiments, as represented in the figures, is not intended to limit the scope of the embodiments, as claimed, but is merely representative of example embodiments.

Reference throughout this specification to “one embodiment” or “an embodiment” (or the like) means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearance of the phrases “in one embodiment” or “in an embodiment” or the like in various places throughout this specification are not necessarily all referring to the same embodiment.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments. One skilled in the relevant art will recognize, however, that the various embodiments can be practiced without one or more of the specific details, or with other methods, components, materials, et cetera. In other instances, well known structures, materials, or operations are not shown or described in detail to avoid obfuscation.

As with virtually any computing environment, issues may arise in speech recognition systems that need to be identified and fixed. More particularly, these systems need to be continually monitored and updated to keep pace with the rapidly evolving nature of language (e.g., as new words or phrases are added to the general lexicon, as new pronunciations or utilizations develop for certain words, etc.). If not maintained, speech recognition systems may be unable to effectively recognize and process audible user commands.

One of the best ways to improve the natural language recognition and processing capabilities of a digital assistant capable of speech recognition is to access and analyze the raw commands provided by the global population of users (e.g., to identify where and/or how the system is failing, to identify aspects of the system individuals use most frequently, etc.). However, access to these commands may lead to issues with respect to user privacy. More particularly, user command inputs may contain virtually anything, including personally identifiable information (“PII”). This may be especially true in situations where a digital assistant incorrectly assumes that a command has been provided and attempts to process the users' utterance.

No solutions currently exist that balance the privacy considerations of the users while still preserving the need to continually improve the speech recognition system associated with the digital assistant. At best, some systems contain “opt-out” options where a user can choose to not have any of their information collected and stored. In these situations, any improvements made to the processing capabilities of the system are facilitated by the interaction data obtained from the remaining population of users that do not opt out. This solution effectively decreases the overall pool of users, thereby hampering the system's ability to efficiently improve. Additionally, the users that have agreed to have their interaction data stored are still not effectively protected from having certain types of PII inadvertently captured.

Accordingly, an embodiment provides a method for anonymizing the raw input text of commands, thereby enabling technicians to access this data without correlating it to any one specific individual. In an embodiment, a user command may be detected at a device. The command may be analyzed and an encrypted form of the text (e.g., the raw text, a normalized version of the text, an alternate version of the text, etc.) associated with the user command may be stored in a data store (e.g., a data table, another storage database, etc.). Responsive to determining that the same text has been detected a predetermined number of times in other commands provided by the user or a multitude of different users, an embodiment may thereafter display an unencrypted transcript of the text in a data table. Such a process dramatically reduces the risk of a speech recognition system capturing and storing PII because any raw text that has been made visible has been provided by multiple users.

The illustrated example embodiments will be best understood by reference to the figures. The following description is intended only by way of example, and simply illustrates certain example embodiments.

While various other circuits, circuitry or components may be utilized in information handling devices, with regard to smart phone and/or tablet circuitry100, an example illustrated inFIG.1includes a system on a chip design found for example in tablet or other mobile computing platforms. Software and processor(s) are combined in a single chip110. Processors comprise internal arithmetic units, registers, cache memory, busses, I/O ports, etc., as is well known in the art. Internal busses and the like depend on different vendors, but essentially all the peripheral devices (120) may attach to a single chip110. The circuitry100combines the processor, memory control, and I/O controller hub all into a single chip110. Also, systems100of this type do not typically use SATA or PCI or LPC. Common interfaces, for example, include SDIO and I2C.

There are power management chip(s)130, e.g., a battery management unit, BMU, which manage power as supplied, for example, via a rechargeable battery140, which may be recharged by a connection to a power source (not shown). In at least one design, a single chip, such as110, is used to supply BIOS like functionality and DRAM memory.

System100typically includes one or more of a WWAN transceiver150and a WLAN transceiver160for connecting to various networks, such as telecommunications networks and wireless Internet devices, e.g., access points. Additionally, devices120are commonly included, e.g., an image sensor such as a camera, audio capture device such as a microphone, etc. System100often includes one or more touch screens170for data input and display/rendering. System100also typically includes various memory devices, for example flash memory180and SDRAM190.

FIG.2depicts a block diagram of another example of information handling device circuits, circuitry or components. The example depicted inFIG.2may correspond to computing systems such as the THINKPAD series of personal computers sold by Lenovo (US) Inc. of Morrisville, NC, or other devices. As is apparent from the description herein, embodiments may include other features or only some of the features of the example illustrated inFIG.2.

The example ofFIG.2includes a so-called chipset210(a group of integrated circuits, or chips, that work together, chipsets) with an architecture that may vary depending on manufacturer (for example, INTEL, AMD, ARM, etc.). INTEL is a registered trademark of Intel Corporation in the United States and other countries. AMD is a registered trademark of Advanced Micro Devices, Inc. in the United States and other countries. ARM is an unregistered trademark of ARM Holdings plc in the United States and other countries. The architecture of the chipset210includes a core and memory control group220and an I/O controller hub250that exchanges information (for example, data, signals, commands, etc.) via a direct management interface (DMI)242or a link controller244. InFIG.2, the DMI242is a chip-to-chip interface (sometimes referred to as being a link between a “northbridge” and a “southbridge”). The core and memory control group220include one or more processors222(for example, single or multi-core) and a memory controller hub226that exchange information via a front side bus (FSB)224; noting that components of the group220may be integrated in a chip that supplants the conventional “northbridge” style architecture. One or more processors222comprise internal arithmetic units, registers, cache memory, busses, I/O ports, etc., as is well known in the art.

InFIG.2, the memory controller hub226interfaces with memory240(for example, to provide support for a type of RAM that may be referred to as “system memory” or “memory”). The memory controller hub226further includes a low voltage differential signaling (LVDS) interface232for a display device292(for example, a CRT, a flat panel, touch screen, etc.). A block238includes some technologies that may be supported via the LVDS interface232(for example, serial digital video, HDMI/DVI, display port). The memory controller hub226also includes a PCI-express interface (PCI-E)234that may support discrete graphics236.

InFIG.2, the I/O hub controller250includes a SATA interface251(for example, for HDDs, SDDs, etc.,280), a PCI-E interface252(for example, for wireless connections282), a USB interface253(for example, for devices284such as a digitizer, keyboard, mice, cameras, phones, microphones, storage, other connected devices, etc.), a network interface254(for example, LAN), a GPIO interface255, a LPC interface270(for ASICs271, a TPM272, a super I/O273, a firmware hub274, BIOS support275as well as various types of memory276such as ROM277, Flash278, and NVRAM279), a power management interface261, a clock generator interface262, an audio interface263(for example, for speakers294), a TCO interface264, a system management bus interface265, and SPI Flash266, which can include BIOS268and boot code290. The I/O hub controller250may include gigabit Ethernet support.

The system, upon power on, may be configured to execute boot code290for the BIOS268, as stored within the SPI Flash266, and thereafter processes data under the control of one or more operating systems and application software (for example, stored in system memory240). An operating system may be stored in any of a variety of locations and accessed, for example, according to instructions of the BIOS268. As described herein, a device may include fewer or more features than shown in the system ofFIG.2.

Information handling device circuitry, as for example outlined inFIG.1orFIG.2, may be used in devices capable of receiving commands from a user and identifying a text correlation from those commands. For example, the circuitry outlined inFIG.1may be implemented in a smart phone or tablet embodiment, whereas the circuitry outlined inFIG.2may be implemented in a laptop computer.

Referring now toFIG.3, a method for ensuring the anonymity of user commands is provided. At301, an embodiment may receive the text associated with the user command. In an embodiment, the user command may be provided by a variety of different input modalities (e.g., audible input, typing input, touching input, handwriting input, etc.) and may be detected using one or more different input detecting means (e.g., a microphone for audible input, a keyboard for typing input, a touch sensitive display for touch and/or handwriting input, etc.). For simplicity purposes, the remainder of this discussion is directed to user voice commands detected by an audio input device (e.g., a microphone, etc.) integrally or operatively coupled to a user's device

In an embodiment, the text associated with the user command may correspond to one of: the raw text of the user command, a normalized version of the raw text, and at least one alternate version of the raw text. In an embodiment, the raw text corresponds to the direct text transcription of the command provided by the user, i.e., what the input recognition system interprets the command to be in text form. For example, the raw text of an audible user command may be the text transcription of what a speech recognition system interprets the audible user command to be. In an embodiment, the raw text may be dynamically normalized (e.g., subject to one or more linguistic processes such as stemming, lemmatization, stop word removal, ordinal conversion, etc.) to produce a normalized version of the raw text. For example, a user command may have the raw text “Computer, set my brightness to eighty” for which a normalized version may be “Set bright 80”. In an embodiment, there may a multitude of different possible text transcripts from the same speech data. Stated differently, a system may identify a multitude of alternate interpretations, or versions, of the raw text associated with the command input. For instance, using the raw text of the foregoing example, alternate versions of that raw text may include: “Computer, set my highness to eighty”, “Computer, set my height less than eighty”, “Computer, set height net to eighty”.

In an embodiment, after the text of a user command has been received at a device, an indication of that text may be transmitted to a remote location (e.g., a cloud computing service, etc.) for additional processing. This remote processing location may therefore be capable of receiving indications of texts of user commands from a predetermined pool of users, e.g., a local pool of users corresponding to a user and their close associates (e.g., their family, work colleagues, etc.), a regional pool of users (e.g., from a user's regional geographic area, state, country, etc.), or a global pool of users.

At302, an embodiment may encrypt the text and store it in a storage location. Although a variety of encryption techniques may be utilized, the remaining discussion is directed toward the encryption of the text as a hash value by utilization of a hashing algorithm, as conventionally known in the art. Subsequent to encryption, the encrypted text may thereafter be stored at a predetermined storage location (e.g., in a data table, another local or remote data store, etc.).

In an embodiment, each unique text associated with a user command may be assigned its own hash value. Accordingly, if the raw text strings of two user commands vary even slightly, each of those commands will receive a separate hash value. For example, User A may provide the command “mute the speakers” whereas User B may provide the command “mute the speaker”. Although both of the foregoing commands effectively map to the same underlying action, each command will receive its own hash value because the raw texts of the commands are different (i.e., one is a pluralized form of the other).

In an embodiment, a hashed form of the text may not be stored in the storage location unless a recognizable action corresponding to the user command is identified. Stated differently, an embodiment may only store the text for user commands that are capable of being processed. This “check” on the system ensures that only user inputs identifiable as commands are stored in the table, thereby limiting the potential for capturing and storing PII. An embodiment may make this determination by accessing a data store of associations between user commands and associated actions.

At303, an embodiment may determine whether the encrypted form of the text has been identified in other user commands a predetermined threshold number of times. In an embodiment, the other user commands may be provided by a single user or they may derive from a plurality of other individuals. To facilitate this determination, each hash value stored in the data table may be accompanied by a frequency counter. Such a counter may be configured to increase its value each time another iteration of the encrypted form of the text is identified. In an embodiment, the predetermined threshold value may be originally set by a programmer and later adjusted by a user of the system.

Responsive to determining, at303, that the encrypted form of the text has not been identified at least a predetermined threshold number of times, an embodiment may, at304, take no additional action. More particularly, an embodiment may continue to keep the transcript of the text hidden from view. Conversely, responsive to determining, at303, that the encrypted form of the text has been identified at least the predetermined threshold number of times, an embodiment may store, at305, an indication of an unencrypted transcript of the text in a data table.

Referring now toFIG.4, a data table as previously mentioned is presented according to an embodiment. In an embodiment, the data table40may contain fields for hash values41, raw text transcripts42, frequency counters for each hash value43, and dates of the last observed iteration of each raw text44. For user commands for which the raw text has been identified at least a predetermined threshold number of times (e.g., where the threshold value utilized inFIG.4may be 1000), an indication of an unencrypted transcript of the raw text of the command may be stored in the data table and may be made visible to authorized personnel upon access. For example, in the data table40, the user commands of “set brightness to max”45, “increase brightness”46, and “set brightness100”47may be visible to an accessing user because each of those commands has a frequency count in excess of the threshold number, i.e.,1000. Conversely, the raw text for the user commands48and49remains hidden because the frequency counts for each of these commands has not yet reached1000.

In another embodiment, additional types of content may also be made visible in the data table. For example, in addition to the raw text, a data table may be able to present a normalized version of the raw text. Accordingly, for each individual command input there may be multiple entries in the database. In this way, overseers of the speech recognition system may be able to see normalized input earlier than the raw input, i.e., because similar but different command inputs may receive their own hash value but still have the same normalized format. Additionally or alternatively, in an embodiment, there may be a multitude of different possible transcripts from the same input data. Stated differently, a system may identify a multitude of alternate interpretations of the raw text of an input command (e.g., a voice command, etc.). Accordingly, a data table may also contain a section of alternates, or “n-best”, versions of the raw command text (e.g., limited to the top three alternatives, etc.).

As an example of the foregoing and with reference toFIG.5, a data table50is provided according to an embodiment. In the data table50, a threshold value to store an indication of a transcript of the raw text data may be 1000. The raw text data for a first command51may be “set brightness to max” and the raw text data for a second command52may be “increase brightness to100”. As can be seen, the raw text data for the first command51may be visible to an accessing user because a frequency counter associated with the first command51has exceeded the threshold amount whereas the raw text data for the second command52remains hidden (i.e., is not stored in the data table50) because the frequency counter for the second command52has not exceeded the threshold amount. The provided data table50also contains fields for the normalized transcripts53as well as fields for the potential alternate transcripts54. Focusing on the former, a data cell for each of the first command51and the second command52may be populated with a normalized transcript of the original raw text data, i.e., “Set Bright100”, regardless of whether either command has been detected the threshold amount of times. Turning to the latter, a list of potential alternative transcripts of the system's interpretation of the original input data may be provided for first command51but not for the second command52(i.e., because the raw text data has been made visible for the first command51).

The various embodiments described herein thus represent a technical improvement to conventional methods for anonymizing the text transcripts of user commands. Using the techniques described herein, an embodiment may detect a user command using an input recognition system and store an encrypted form of the text of the user command in a storage location. An embodiment may then determine whether the encrypted form of the text of the user command has been detected by the input recognition system a predetermined number of times (e.g., via multiple provisions of the user command by a single user or one or more other individuals, etc.). If it has not, an embodiment may not store an indication of the text of the user command in a data table. If it has, an embodiment may store an unencrypted transcript of the raw text in the data table, which may be visible to a user upon access and analysis of the data table. Such a method may ensure that only the text data of user commands that have been received numerous times are stored, thereby preserving user privacy.

As will be appreciated by one skilled in the art, various aspects may be embodied as a system, method or device program product. Accordingly, aspects may take the form of an entirely hardware embodiment or an embodiment including software that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects may take the form of a device program product embodied in one or more device readable medium(s) having device readable program code embodied therewith.

It should be noted that the various functions described herein may be implemented using instructions stored on a device readable storage medium such as a non-signal storage device that are executed by a processor. A storage device may be, for example, a system, apparatus, or device (e.g., an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device) or any suitable combination of the foregoing. More specific examples of a storage device/medium include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a storage device is not a signal and “non-transitory” includes all media except signal media.

Program code embodied on a storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, et cetera, or any suitable combination of the foregoing.

Program code for carrying out operations may be written in any combination of one or more programming languages. The program code may execute entirely on a single device, partly on a single device, as a stand-alone software package, partly on single device and partly on another device, or entirely on the other device. In some cases, the devices may be connected through any type of connection or network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made through other devices (for example, through the Internet using an Internet Service Provider), through wireless connections, e.g., near-field communication, or through a hard wire connection, such as over a USB connection.

Example embodiments are described herein with reference to the figures, which illustrate example methods, devices and program products according to various example embodiments. It will be understood that the actions and functionality may be implemented at least in part by program instructions. These program instructions may be provided to a processor of a device, a special purpose information handling device, or other programmable data processing device to produce a machine, such that the instructions, which execute via a processor of the device implement the functions/acts specified.

It is worth noting that while specific blocks are used in the figures, and a particular ordering of blocks has been illustrated, these are non-limiting examples. In certain contexts, two or more blocks may be combined, a block may be split into two or more blocks, or certain blocks may be re-ordered or re-organized as appropriate, as the explicit illustrated examples are used only for descriptive purposes and are not to be construed as limiting.

As used herein, the singular “a” and “an” may be construed as including the plural “one or more” unless clearly indicated otherwise.

This disclosure has been presented for purposes of illustration and description but is not intended to be exhaustive or limiting. Many modifications and variations will be apparent to those of ordinary skill in the art. The example embodiments were chosen and described in order to explain principles and practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.

Thus, although illustrative example embodiments have been described herein with reference to the accompanying figures, it is to be understood that this description is not limiting and that various other changes and modifications may be affected therein by one skilled in the art without departing from the scope or spirit of the disclosure.