Method, apparatus and wearable device for controlling a wearable device

Abstract

This disclosure provides a method, apparatus, and wearable device for controlling a wearable device, relating to the field of device control. The method for controlling a wearable device includes: acquiring a first voice signal received at a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; acquiring a second voice signal received at a second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; determining a correlation between the first voice signal and the second voice signal; and controlling the wearable device based on the correlation between the first voice signal and the second voice signal, and the second voice signal.

Description

Technical Field

[0001] This disclosure relates to the field of device control, and more particularly to a method, apparatus, wearable device, storage medium, and program product for controlling wearable devices. Background Technology

[0002] Wearable devices such as headphones are widely used, but in real life, wearers can control the wearable device, while other users may also control it, which can interfere with the wearer's interaction with the wearable device and thus affect the overall experience. Summary of the Invention

[0003] According to some embodiments of this disclosure, a method for controlling a wearable device is provided, comprising: acquiring a first voice signal received at a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; acquiring a second voice signal received at a second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; determining a correlation between the first voice signal and the second voice signal; and controlling the wearable device based on the correlation between the first voice signal and the second voice signal and the second voice signal.

[0004] According to other embodiments of this disclosure, an apparatus for controlling a wearable device is provided, comprising: a first voice signal acquisition module configured to acquire a first voice signal received at a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; a second voice signal acquisition module configured to acquire a second voice signal received at a second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; a correlation determination module configured to determine the correlation between the first voice signal and the second voice signal; and a control module configured to control the wearable device based on the correlation between the first voice signal and the second voice signal and the second voice signal.

[0005] According to further embodiments of the present disclosure, an apparatus for controlling a wearable device is provided, comprising: a processor; and a memory coupled to the processor, the processor being configured to perform a method for controlling a wearable device according to any embodiment of the present disclosure based on instructions stored in the memory.

[0006] According to further embodiments of the present disclosure, a wearable device is provided, comprising: means for controlling the wearable device according to any embodiment of the present disclosure; a first input terminal configured to receive a first voice signal, wherein the first voice signal is a bone conduction signal; and a second input terminal configured to receive a second voice signal, wherein the second voice signal is a non-bone conduction signal.

[0007] According to further embodiments of the present disclosure, a computer-readable storage medium is provided having computer program instructions stored thereon that, when executed by a processor, implement a method for controlling a wearable device according to any embodiment of the present disclosure.

[0008] According to further embodiments of the present disclosure, a computer program product is provided, including a computer program or instructions that, when executed by a processor, implement a method for controlling a wearable device according to any embodiment of the present disclosure.

[0009] Other features, aspects, and advantages of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0010] Embodiments of this disclosure are described below with reference to the accompanying drawings. It should be understood that the drawings described below are merely illustrative of some embodiments of this disclosure and are not intended to limit the scope of this disclosure. In the drawings:

[0011] Figure 1 A flowchart illustrating a method for controlling a wearable device according to some embodiments of the present disclosure is shown.

[0012] Figure 2 A schematic diagram illustrating the process of determining the correlation between a first speech signal and a second speech signal according to some embodiments of this disclosure is shown.

[0013] Figure 3 The diagram illustrates a process for controlling a wearable device according to some embodiments of this disclosure;

[0014] Figure 4 A flowchart illustrating a method for controlling a wearable device according to some embodiments of the present disclosure is shown;

[0015] Figure 5 A schematic diagram illustrating the process of controlling the output of speech content in a second speech signal according to some embodiments of this disclosure is shown.

[0016] Figure 6 A schematic diagram illustrating a method for controlling a wearable device according to some embodiments of this disclosure;

[0017] Figure 7 A block diagram illustrating an apparatus for controlling a wearable device according to some embodiments of the present disclosure;

[0018] Figure 8 Block diagrams illustrating apparatus for controlling wearable devices according to other embodiments of this disclosure;

[0019] Figure 9 Block diagrams of wearable devices according to some embodiments of the present disclosure are shown;

[0020] Figure 10 A block diagram of an electronic device according to some embodiments of the present disclosure is shown.

[0021] It should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not necessarily drawn to actual scale. The same or similar reference numerals are used in the various drawings to denote the same or similar parts. Therefore, once an item is defined in one drawing, it may not be discussed further in subsequent drawings. Detailed Implementation

[0022] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. It should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein.

[0023] It should be understood that the various steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect. Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of components and steps set forth in these embodiments should be interpreted as merely exemplary and do not limit the scope of this disclosure.

[0024] As used in this disclosure, the term "comprising" and its variations are open-ended terms that include at least the following elements / features but do not exclude other elements / features, i.e., "including but not limited to". The term "based on" means "at least partially based on".

[0025] It should be noted that the concepts of "first," "second," etc., used in this disclosure are used only to distinguish different devices, modules, or units, and are not intended to define the order of functions performed by these devices, modules, or units or their interdependencies. Unless otherwise specified, the concepts of "first," "second," etc., are not intended to imply that the objects described herein must be in a given temporal, spatial, rank, or any other given order.

[0026] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0027] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0028] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals shall be provided for users to choose to authorize or refuse.

[0029] The embodiments of this disclosure are described in detail below with reference to the accompanying drawings; however, this disclosure is not limited to these specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. Furthermore, in one or more embodiments, specific features, structures, or characteristics can be combined in any suitable manner that will be apparent to those skilled in the art from this disclosure.

[0030] To achieve voice control of wearable devices, it's necessary to first identify whether the wearer is speaking. Related technologies determine this by detecting the energy level of the bone conduction signal. However, in some hardware scenarios, the energy of the bone conduction signal can be unstable. Therefore, relying solely on the energy level of the bone conduction signal cannot accurately identify whether the wearer is speaking, potentially leading to unintended control of the wearable device.

[0031] The embodiments of this disclosure provide a method for controlling wearable devices, which enables accurate control of wearable devices and reduces the occurrence of miscontrol.

[0032] Figure 1 Flowcharts illustrating some embodiments of the method for controlling wearable devices according to this disclosure. Figure 1 As shown, the method of this embodiment includes: step S11, acquiring a first voice signal received by a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; step S12, acquiring a second voice signal received by a second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; step S13, determining the correlation between the first voice signal and the second voice signal; and step S14, controlling the wearable device based on the correlation between the first voice signal and the second voice signal and the second voice signal.

[0033] In the above embodiments, the wearer of the wearable device is identified as speaking based on the correlation between the two voice signals, and then the wearable device is controlled based on the second voice signal. This enables the wearer to control the wearable device with their own commands, thereby improving the wearer's experience.

[0034] The following section will describe methods for controlling wearable devices with specific examples.

[0035] The wearable device is, for example, a headphone, hearing aid, AR (Augmented Reality) device, VR (Virtual Reality) device, or any other device with a bone conduction sensor.

[0036] In step S11, the first input terminal is, for example, a bone conduction microphone, which can pick up speech signals and generate bone conduction signals. The bone conduction microphone is, for example, a VPU (Voice Pick-up Unit) microphone, which can extract speech information with high quality in noisy environments.

[0037] Bone conduction is a sound transmission method that converts sound into mechanical vibrations of different frequencies, transmitting sound waves through the skull, bony labyrinth, inner ear fluid, cochlea, and auditory center. Compared to the classic sound conduction method that generates sound waves through a diaphragm, bone conduction eliminates many steps in sound wave transmission, enabling clear sound reproduction in noisy environments, and the sound waves do not affect others due to airborne diffusion. Therefore, the bone conduction signal is typically the wearer's own voice signal.

[0038] In step S12, the second input terminal is capable of receiving non-bone conduction signals, such as air conduction signals. This second input terminal is, for example, a standard microphone. A standard microphone is an energy conversion device that converts sound signals into electrical signals.

[0039] In some embodiments, the second input is a microphone with lower received voice signal energy, which is either a directional microphone or an omnidirectional microphone.

[0040] Wearable devices can include three microphones, such as a VPU microphone, a directional microphone, and an omnidirectional microphone. A directional microphone is a type of microphone that can precisely capture sound from a specific direction and suppress noise from other directions. An omnidirectional microphone is a multi-directional microphone that can capture sound from multiple directions. The performance of directional and omnidirectional microphones varies in different scenarios, and a microphone with lower energy can be selected for subsequent signal processing based on the specific scenario. A microphone with lower energy is also a microphone with lower noise. The speech signal received by a microphone with lower noise is more convenient and accurate for subsequent processing. In this embodiment, by selecting a non-bone conduction signal, the accuracy of subsequent signal processing can be improved.

[0041] In step S13, for example, the correlation between the first speech signal and the second speech signal can be determined using a correlation algorithm. This disclosure does not limit the correlation algorithm used to calculate the correlation between the first speech signal and the second speech signal.

[0042] Since bone conduction signals are usually the wearer's own voice signals, if the second voice signal also includes the wearer's own voice signal, the correlation between the first and second voice signals is relatively high; if the second voice signal does not include the wearer's own voice signal, the correlation between the first and second voice signals is relatively low.

[0043] To improve the accuracy of signal correlation calculation, the method for controlling wearable devices further includes performing AEC (Acoustic Echo Cancellation) processing on the first and second speech signals before determining the correlation between them.

[0044] AEC (Acoustic Echo Cancellation) technology can reduce or eliminate echoes in speech signals by identifying and removing echo components to clarify the speech signal. This embodiment does not limit the AEC algorithm; those skilled in the art can use relevant AEC algorithms to perform acoustic echo cancellation processing on speech signals to improve signal clarity and thus enhance the accuracy of subsequent signal correlation assessments.

[0045] In step S14, for example, if the correlation between the first voice signal and the second voice signal is greater than a first threshold, it indicates that the wearer is attempting to control the wearable device, and the wearable device can be controlled in this case. If the correlation between the first voice signal and the second voice signal is less than or equal to the first threshold, it indicates that the wearer is not speaking, and the wearable device should not be controlled in this case.

[0046] For example, if the second voice signal is identified and contains a control instruction, then if the correlation between the first voice signal and the second voice signal is greater than a first threshold, the wearable device is controlled according to the control instruction.

[0047] In the above embodiments, by utilizing the correlation between the two types of speech signals, it is possible to identify whether the wearer of the wearable device is speaking even when the energy of the bone conduction signal is low, thereby reducing the occurrence of mis-controlling the device due to the inaccuracy of recognizing a single type of speech signal.

[0048] In some embodiments, the energy of bone conduction signals can be used to determine the wearer's speaking state first, and then the correlation between the two types of speech signals can be used to assist in determining the wearer's speaking state. By combining the two determination methods, the accuracy of determining the wearer's speaking state can be improved.

[0049] The processing of speech signals is a streaming process, meaning that each speech signal consists of multiple frames, and the correlation of individual frames can be calculated. Below, we will combine... Figure 2 The correlation between the first and second speech signals is introduced.

[0050] Figure 2 This diagram illustrates a flowchart of some embodiments of the present disclosure for determining the correlation between a first speech signal and a second speech signal. Step S13 includes step S131, which will be described below. Figure 2 and Figure 1 The differences are minor, while the similarities will not be elaborated upon.

[0051] In step S131, the correlation between a single frame signal of the first speech signal and the corresponding frame signal of the second speech signal at the same time is determined.

[0052] For example, the first speech signal is calculated according to formula (1). The first frame The frame signal at each frequency point and the second speech signal at the first frequency point The first frame Correlation coefficient of frame signals at each frequency point ,in, A positive integer greater than or equal to 1. It is a positive integer greater than or equal to 1.

[0053] (1)

[0054] in,

[0055] For smoothing parameters, The value can be 1 or 2. The value can be 1 or 2. Indicates the first speech signal. Indicates the second speech signal. This indicates the conjugate transpose. The first speech signal The first frame The frame signal at each frequency point and the second speech signal at the first frequency point The first frame The covariance of the frame signal at each frequency point The first speech signal represents the... The first frame The frame signal at each frequency point and the second speech signal at the first frequency point The first frame The autocovariance of the frame signal at each frequency point.

[0056] After calculating the first speech signal, The first frame The frame signal at each frequency point and the second speech signal at the first frequency point The first frame Correlation coefficient of frame signals at each frequency point Then, the correlation of each frequency point in each frame of the signal can be averaged to obtain the first frequency point of the first speech signal. The frame signal of the second speech signal and the first frame of the second speech signal The correlation coefficient of the frame signal of a frame .

[0057] Those skilled in the art should understand that, in order to make the first speech signal... The frame signal of the second speech signal and the first frame of the second speech signal The correlation coefficient of the frame signal of a frame For greater accuracy, further research is also possible. The smoothing process is performed, but the specific implementation details are not described further in this embodiment.

[0058] Those skilled in the art should understand that there are various formulas for calculating the correlation between two signals. The above formula is only for example. Those skilled in the art can choose the corresponding formula to calculate the correlation between two speech signals according to the actual situation.

[0059] The state of the current frame can be determined based on the correlation between speech signals.

[0060] In some embodiments, if the first voice signal of the first voice signal The frame signal of the second speech signal and the first frame of the second speech signal If the correlation of the frame signals of the second speech signal is greater than the first threshold, then it indicates that the second speech signal is in the first frame. The frame signal of the first frame is the signal output by the wearer, and the state of the current frame can be set to 1. If the first voice signal... The frame signal of the second speech signal and the first frame of the second speech signal If the correlation of the frame signals of the second speech signal is less than or equal to the first threshold, then it indicates that the second speech signal is in the first frame. If the frame signal is not the signal output by the wearer, the state of the current frame can be set to 0.

[0061] The first threshold is, for example, 0.5. Those skilled in the art should understand that this value is merely an example and can be adjusted according to actual circumstances, such as accuracy requirements. For instance, if higher accuracy is required, the value of the first threshold can be increased, for example, to 0.6, 0.7, 0.8, 0.9, etc. If lower accuracy is required, the value of the first threshold can be decreased, for example, to 0.3, 0.4, 0.45, etc.

[0062] In real-time interactive scenarios, speech is processed frame by frame, but the processing result of a single frame signal may fluctuate. Therefore, in some embodiments of this disclosure, the correlation between the calculated first speech signal and the second speech signal is smoothed to improve the stability of the judgment result. The following will use... Figure 3 Let's take an example to illustrate.

[0063] Figure 3 This disclosure illustrates a flowchart of controlling a wearable device according to some embodiments of the present disclosure. Figure 1 Step S14 will be further described below, which includes steps S141 and S142. Only steps S141 and S142 will be described below. Figure 3 and Figure 1 The differences are minor, while the similarities will not be elaborated upon.

[0064] In step S141, the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than the first threshold is determined.

[0065] For example, for a series of consecutive frames, since the correlation between a single frame of the first speech signal and the corresponding frame of the second speech signal at the same time has been calculated, the series of consecutive frames can be judged, that is, the number of frames in the series of frames of the first speech signal whose correlation with the corresponding frame of the second speech signal is greater than a first threshold can be judged.

[0066] In some embodiments, the number of the multi-frame signals is determined according to the control delay requirements of the wearable device.

[0067] For example, when controlling wearable devices, although multi-frame signals are smoothed, the latency after smoothing is lower than the control latency requirements of the device. This balances stability and improves user experience, reducing the occurrence of situations where excessive pursuit of stability leads to excessive latency and poor user experience.

[0068] In some embodiments, the multi-frame signal is, for example, a 6-frame signal, meaning that smoothing is performed once every 6 frames. Those skilled in the art should understand that the number of frame signals here is merely an example, and the number of frame signals for smoothing can be determined according to actual circumstances.

[0069] In step S142, in response to the number of frames being greater than the second threshold and the second voice signal containing a control instruction, the wearable device is controlled.

[0070] For example, if the number of frames in the multi-frame signal of the first voice signal whose correlation with the corresponding frame signal of the second voice signal is greater than a first threshold is greater than a second threshold, it indicates that the wearer of the wearable device is speaking. If the second voice signal contains control instructions, the wearable device can be controlled.

[0071] The setting of this second threshold is related to the number of frames of signal. Those skilled in the art should understand that the value of the second threshold can be adjusted according to accuracy or stability requirements. For example, if high accuracy or stability is required, the value of the second threshold is increased. If low accuracy or stability is required, the value of the second threshold is decreased.

[0072] For example, it can also be determined whether a predetermined proportion of the frames in the multi-frame signal of the first speech signal have a correlation greater than a first threshold with the corresponding frames in the second speech signal. Those skilled in the art should understand that determining whether a predetermined proportion of the frames in the multi-frame signal of the first speech signal have a correlation greater than a first threshold with the corresponding frames in the second speech signal is equivalent to determining whether the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frames in the second speech signal is greater than a second threshold is greater than a second threshold.

[0073] If a predetermined proportion of the frames in the first voice signal have a correlation greater than a first threshold with the corresponding frames in the second voice signal, it indicates that the wearer of the wearable device is speaking. If the second voice signal contains control instructions, the wearable device can be controlled.

[0074] For example, taking frame state as an example, if the correlation between a single frame signal of the first speech signal and the corresponding frame signal in the second speech signal is greater than a first threshold, then the state of the current frame is 1. If the correlation between a single frame signal of the first speech signal and the corresponding frame signal in the second speech signal is less than or equal to the first threshold, then the state of the current frame is 0. The state detection results of multiple frames are added together. If the sum is greater than a certain threshold, it indicates that the wearer of the wearable device is speaking. Therefore, if the second speech signal contains control instructions, the wearable device can be controlled.

[0075] In the above embodiments, by determining the correlation between a single frame signal of the first speech signal and the corresponding frame signal of the second speech signal at the same time, it is possible to determine whether the wearer of the wearable device is speaking at the time corresponding to the current frame. This allows for smoothing of the judgment results of multiple frames, reducing the possibility of miscontrol due to the instability of single frame processing results, improving the robustness and stability of the wearer's speaking state judgment, and thus improving the stability of wearable device control.

[0076] In some embodiments, the control indication is, for example, a wake-up indication. By determining the correlation, it is possible to promptly identify whether to wake up the wearable device, reducing interference from other non-wearers and improving the user experience for the wearer.

[0077] In real life, wearers can use wearable devices to interact with other devices or applications via voice. However, this voice interaction may be disrupted by non-wearers. The following will combine... Figure 4 This paper further introduces the method for controlling wearable devices.

[0078] Figure 4 The following is a flowchart illustrating a method for controlling a wearable device according to some embodiments of the present disclosure. This embodiment includes step S15 in addition to steps S11-S13. Only the following description is provided. Figure 4 and Figure 1 The differences are minor, while the similarities will not be elaborated upon.

[0079] In step S15, the output of the speech content in the second speech signal is controlled according to the correlation between the first speech signal and the second speech signal.

[0080] For example, speech recognition can be performed on the speech content in the second speech signal. This speech recognition process can be executed in the cloud, thereby reducing the consumption of local device resources. Of course, if local resources are sufficient, for example, if the controller of a wearable device has sufficient computing power, the speech recognition process can also be executed locally.

[0081] This embodiment does not limit the speech recognition algorithm, and those skilled in the art can use speech recognition algorithms in related technologies to recognize the content in the second speech signal.

[0082] If the correlation between the first and second voice signals is greater than a first threshold, it indicates that the wearer of the wearable device is speaking. In this case, the output of the voice content in the second voice signal can be controlled. For example, the voice content can be displayed in an application.

[0083] In the above embodiments, by utilizing the correlation between the two types of speech signals, it is possible to identify whether the speech content is output by the wearer of the wearable device, even when the energy of the bone conduction signal is low, thereby improving the accuracy of voice interaction.

[0084] In real-time interactive scenarios, speech is processed frame by frame, but the processing results of a single frame signal may fluctuate. Therefore, in some embodiments of this disclosure, the correlation between the first and second speech signals is smoothed to improve the stability of speech content recognition and output. The following will combine... Figure 5 Step S15 will be described in more detail.

[0085] Figure 5 This diagram illustrates a flowchart of some embodiments of the present disclosure for controlling the output of speech content in a second speech signal. Step S15 includes step S151. The following will only describe... Figure 5 and Figure 1 The differences are minor, while the similarities will not be elaborated upon.

[0086] In step 151, in response to the fact that the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than the first threshold is greater than the third threshold, the speech content in the second speech signal is output.

[0087] The step of determining the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than a first threshold can be performed in the cloud or locally.

[0088] In some embodiments, the number of multi-frame signals is determined based on the cloud-based voice recognition latency requirements of the wearable device.

[0089] For example, when a wearer interacts with an application through a wearable device, although multiple frames of signals are smoothed, the latency after smoothing is lower than the latency requirement of cloud-based voice recognition. This balances stability and latency requirements, improving user experience and reducing the occurrence of situations where excessive pursuit of stability leads to excessive latency and poor user experience.

[0090] For example, since speech recognition inherently has a relatively large delay, 50 frames of signal can be used for smoothing. Those skilled in the art should understand that the value of the number of multiple frames of signal here is only for example and can be set according to the actual situation.

[0091] If the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than the first threshold is greater than the third threshold, it indicates that the wearer of the wearable device is speaking, and the speech content recognized by the speech recognition module can be output.

[0092] The setting of this third threshold is related to the number of frames of signal. Those skilled in the art should understand that the value of the third threshold can be adjusted according to accuracy or stability requirements. For example, if high accuracy or stability is required, the value of the third threshold should be increased. If low accuracy or stability is required, the value of the third threshold should be decreased.

[0093] For example, if a predetermined proportion of the frames in the first voice signal have a correlation greater than a first threshold with the corresponding frames in the second voice signal, it indicates that the wearer of the wearable device is speaking, and the voice content recognized by the voice recognition module can be output.

[0094] Those skilled in the art should understand that the determination made using a predetermined proportion of frame signals in this embodiment is interchangeable with the determination made using the number of frames in the previous embodiment.

[0095] For example, taking frame state as an example, if the correlation between a single frame signal of the first speech signal and the corresponding frame signal in the second speech signal is greater than a first threshold, then the state of the current frame is 1. If the correlation between a single frame signal of the first speech signal and the corresponding frame signal in the second speech signal is less than or equal to the first threshold, then the state of the current frame is 0. The state detection results of multiple frames are added together. If the sum is greater than a certain threshold, it indicates that the wearer of the wearable device is speaking, and the speech content recognized by the speech recognition module can then be output. For example, taking a smoothing of 50 frames as an example, the state detection results of these 50 frames are added together. If the sum is greater than 24, it is considered that the wearer is speaking.

[0096] In the above embodiments, by calculating the correlation between a single frame signal of the first speech signal and the corresponding frame signal of the second speech signal at the same time, it is possible to determine whether the wearer of the wearable device is speaking at the time corresponding to the current frame. In this way, the judgment results of multiple frames are smoothed, which can reduce the situation of erroneous output caused by the instability of single frame processing results, improve the robustness and stability of the judgment of the wearer's speaking state, and thus improve the accuracy of speech content output.

[0097] To improve the accuracy of speech recognition, the timing of the first and last characters in the second speech signal can be identified first, so that only the speech content between the first and last characters is output. In some embodiments, the timing of the first and last characters in the second speech signal is determined based on the correlation between the first speech signal and the corresponding frame signal of the second speech signal in multiple frames of the first speech signal.

[0098] For example, the cloud determines the time points of the first and last characters in the second voice signal based on the correlation between the first and second voice signals, and uses the time points of the first and last characters to help identify the voice content output by the wearer.

[0099] The time point of the first character is the coordinate of the first character, and the time point of the last character is the coordinate of the last character. For example, based on the correlation between frame signals, it is possible to determine when the wearer starts speaking and when they stop speaking. Thus, by using the time points of the first and last characters in the wearer's speech signal, the first and last characters in the second speech signal can be identified, reducing interference and improving the accuracy of speech content recognition.

[0100] To improve the stability of the link, in some embodiments, the method for controlling the wearable device further includes: terminating the output of the voice content in response to the current time point being greater than the time point of the last word in the second voice signal.

[0101] For example, in determining the end of the wearer's speech, it can identify whether the time point of the last word in the second speech signal is more than 500ms away from the current time. That is, if no speech is detected from the wearer for 500ms, it is determined that the speech has ended, thereby ending the output of the speech content and making the interaction link more stable.

[0102] The method for controlling wearable devices disclosed herein will now be described with reference to a specific embodiment.

[0103] like Figure 6 As shown, Figure 6 The diagram illustrates a link diagram of a method for controlling a wearable device according to some embodiments of the present disclosure. The wearable device includes three microphones, such as a VPU microphone, an omnidirectional microphone, and a directional microphone.

[0104] The bone conduction signal received by the VPU microphone is processed by the first AEC algorithm module 611 to obtain the bone conduction signal after acoustic echo cancellation. The first signal received by the omnidirectional microphone is processed by the second AEC algorithm module 612 to obtain the first signal after acoustic echo cancellation. The second signal received by the directional microphone is processed by the third AEC algorithm module 613 to obtain the second signal after acoustic echo cancellation.

[0105] The signal selection module 62 selects between the first signal and the second signal after acoustic echo cancellation to obtain a selected signal. The correlation detection algorithm module 63 calculates the correlation between a single frame signal of the bone conduction signal after acoustic echo cancellation and the corresponding frame signal of the selected signal at the same time. For example, if the correlation is greater than 0.5, the state of the current frame signal is determined to be 1, i.e., the wearer's speaking state is 1; if the correlation is less than or equal to 0.5, the state of the current frame signal is determined to be 0, i.e., the wearer's speaking state is 0.

[0106] Since judging the wearer's speaking status on a frame-by-frame basis can be volatile, leading to unstable judgment results, the status detection results can be smoothed separately from the device and the cloud.

[0107] For example, the first smoothing strategy module 64 sums the states of multiple frames of signals to identify the wearer's speaking state, i.e., whether the wearer is speaking. For example, if smoothing is performed on 6 frames of signals, and the sum of the state detection results of the 6 frames is greater than 2, then the wearer is considered to be speaking. This first smoothing strategy module 64 is located on the device side.

[0108] For example, the second smoothing strategy module 65 sums the states of multiple frames of signals to identify the wearer's speaking state, i.e., whether the wearer is speaking. For instance, if 60 frames of signals are smoothed once, and the sum of the state detection results of the 60 frames is greater than 24, then the wearer is considered to be speaking. The second smoothing strategy module 65 is located in the cloud.

[0109] The latency requirements of the cloud and the device are different, so the smoothing strategies are different. However, the latency smoothed on the device is lower than the wake-up latency on the device, and the latency smoothed in the cloud is lower than the latency of the cloud recognition result.

[0110] The selection signal output by the signal selection module 62 is processed through two separate links. For example, the wake-up module 66 of the voice wake-up link identifies whether the selection signal contains a wake-up indication. If the selection signal contains a wake-up state, and the first smoothing strategy module 64 identifies that the wearer is speaking, the wearable device is woken up. After waking up the wearable device, the voice recognition module 67 of the voice recognition link recognizes the voice content. If the second smoothing strategy module 65 identifies that the wearer is speaking, the voice content is output. This voice recognition link is a cloud processing link.

[0111] In the above embodiments, a microphone and software processing module are used to detect the speaking state of the wearer in a hardware-software coordinated manner. The correlation between two types of voice signals is used to identify the wearer's speaking state, and different state detection smoothing strategies are designed for the on-device and cloud links, making the overall speaking state judgment more robust and stable, and realizing a voice interaction function targeted at the wearer.

[0112] Those skilled in the art will understand that, in the methods described in the specific embodiments, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0113] The above are some embodiments of the method for controlling wearable devices provided in this disclosure. The following will be combined with... Figure 7 This disclosure describes means for controlling wearable devices in some embodiments.

[0114] Figure 7 Block diagrams illustrating apparatus for controlling wearable devices according to some embodiments of the present disclosure, such as Figure 7 As shown, the device 7 for controlling the wearable device includes a first acquisition module 71, a second acquisition module 72, a correlation determination module 73, and a control module 74.

[0115] The first acquisition module 71 is configured to acquire a first voice signal received by a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; the second acquisition module 72 is configured to acquire a second voice signal received by a second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; the correlation determination module 73 is configured to determine the correlation between the first voice signal and the second voice signal; and the control module 74 is configured to control the wearable device based on the correlation between the first voice signal and the second voice signal and the second voice signal.

[0116] The device for controlling the wearable device can be a controller installed on the wearable device, or it can include control and computing components located in the cloud. This device for controlling the wearable device can be used to perform... Figure 1 Steps S11 to S14.

[0117] This device for controlling wearable devices utilizes the correlation between two types of voice signals, enabling it to identify whether the wearer is speaking even when the bone conduction signal energy is low, thus reducing the occurrence of mis-controlling the device due to inaccuracies in recognizing a single voice signal.

[0118] In some embodiments, the first input is a VPU microphone.

[0119] In some embodiments, the second input is a microphone with lower received voice signal energy, either a directional microphone or an omnidirectional microphone, thereby reducing noise in the second voice signal.

[0120] In some embodiments, the correlation determination module 73 is configured to determine the correlation between a single frame signal of the first speech signal and a corresponding frame signal of the second speech signal at the same time.

[0121] If the correlation between the current frame signal of the first voice signal and the current frame signal of the second voice signal is greater than a first threshold, it indicates that the current frame signal of the second voice signal is a signal output by the wearer. If the correlation between the current frame signal of the first voice signal and the current frame signal of the second voice signal is less than or equal to the first threshold, it indicates that the current frame signal of the second voice signal is not a signal output by the wearer.

[0122] In some embodiments, the control module 74 is configured to determine the number of frames in the multi-frame signal of the first voice signal whose correlation with the corresponding frame signal of the second voice signal is greater than a first threshold; and to control the wearable device in response to the number of frames being greater than a second threshold and the second voice signal containing a control instruction.

[0123] In real-time interactive scenarios, speech is processed frame by frame, but the processing result of a single frame signal is unstable and fluctuates. Therefore, this embodiment performs smoothing processing on the correlation between the first and second speech signals to improve the stability of the judgment result.

[0124] In some embodiments, the number of multi-frame signals is determined based on the control latency requirements of the wearable device. This embodiment balances the stability of the judgment with latency requirements, thereby improving the user experience.

[0125] In some embodiments, the control indication includes a wake-up indication, thereby enabling a wake-up operation on the wearable device.

[0126] In some embodiments, the control module 74 is further configured to control the output of speech content in the second speech signal based on the correlation between the first speech signal and the second speech signal.

[0127] For example, if the correlation between the first speech signal and the second speech signal is greater than the first threshold, it indicates that the wearer of the wearable device is speaking. In this case, the output of the speech content in the second speech signal can be controlled.

[0128] In the above embodiments, by utilizing the correlation between the two types of speech signals, it is possible to identify whether the wearer of the wearable device is speaking even when the energy of the bone conduction signal is low, thereby improving the accuracy of voice interaction.

[0129] In some embodiments, the control module 74 is further configured to output the speech content in the second speech signal in response to a third threshold being greater than the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than a first threshold.

[0130] In the above embodiments, by calculating the correlation between a single frame signal of the first speech signal and the corresponding frame signal of the second speech signal at the same time, it is possible to determine whether the wearer of the wearable device is speaking at the time corresponding to the current frame. In this way, the judgment results of multiple frames are smoothed, which can reduce the situation of erroneous output caused by the instability of single frame processing results, improve the robustness and stability of the judgment of the wearer's speaking state, and thus improve the accuracy of speech content output.

[0131] In some embodiments, the number of multi-frame signals is determined based on the cloud-based voice recognition latency requirements of the wearable device. This embodiment balances the stability of the judgment with latency requirements, thereby improving the user experience.

[0132] In some embodiments, the time points of the first and last characters in the second speech signal are determined based on the correlation between the first speech signal and the corresponding frame signal of the second speech signal in the multi-frame signal.

[0133] The time point of the first character is the coordinate of the first character, and the time point of the last character is the coordinate of the last character. For example, based on the correlation between frame signals, it is possible to determine when the wearer starts speaking and when they stop speaking. Thus, by using the time points of the first and last characters in the wearer's speech signal, the first and last characters in the second speech signal can be identified, reducing interference and improving the accuracy of speech content recognition.

[0134] In some embodiments, the control module 74 is further configured to terminate the output of the speech content in response to the current time point being greater than the time point of the last word in the second speech signal.

[0135] It should be noted that the above-described units are merely logical modules divided according to their specific functions, and are not intended to limit the specific implementation method. For example, they can be implemented in software, hardware, or a combination of both. In actual implementation, the above-described units can be implemented as independent physical entities, or they can be implemented by a single entity (e.g., a processor (CPU or DSP, etc.), integrated circuit, etc.). Furthermore, the units shown in the accompanying drawings with dashed lines indicate that these units may not actually exist, and the operations / functions they perform can be implemented by the processing circuitry itself.

[0136] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to. For the sake of brevity, this disclosure will not repeat them.

[0137] This disclosure also provides a device for controlling wearable devices, which is described below in conjunction with... Figure 8 Describe it.

[0138] Figure 8 Block diagrams illustrating apparatus for controlling wearable devices according to other embodiments of this disclosure are shown. Figure 8 As shown, the device 8 for controlling a wearable device includes a memory 81 and a processor 82 coupled to the memory. The processor 82 is configured to execute the method for controlling the wearable device according to any of the above embodiments based on instructions stored in the memory.

[0139] Memory 81 is used to store one or more computer-readable instructions. Memory 81 may include any combination of various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory, including but not limited to random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), and flash memory. Memory 81 may, for example, store operating systems, application programs, bootloaders, databases, and other programs, as well as various application programs and various data.

[0140] The processor 82 is configured to execute computer-readable instructions to implement the method for controlling a wearable device as described in any of the foregoing embodiments or the method described in any of the foregoing embodiments. Specific implementations of each step of the method can be found in the above embodiments, and repeated details will not be elaborated here.

[0141] Processor 82 can be configured to execute Figures 1 to 6 The processor 82 can be various processing devices, such as a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The central processing unit (CPU) can be based on x86 or ARM architectures, etc.

[0142] The processor 82 and the memory 81 can communicate with each other directly or indirectly. For example, the processor 82 and the memory 81 can communicate via a network. The network can include wireless networks, wired networks, and / or any combination of wireless and wired networks. The processor 82 and the memory 81 can also communicate with each other via a system bus, which is not limited in this disclosure.

[0143] It should be noted that Figure 8The components of the device 8 for controlling the wearable device shown are merely exemplary and not limiting. The device 8 may have other components depending on the specific application requirements. The processor 82 can control other components in the device 8 for controlling the wearable device to perform desired functions.

[0144] The device for controlling wearable devices can be implemented by software, firmware, and / or hardware, and can be integrated into a device with the relevant application installed.

[0145] Figure 9 Block diagrams of wearable devices according to some embodiments of this disclosure are shown, such as Figure 9 As shown, the wearable device 9 includes a device 91 for controlling the wearable device in the above embodiments, as well as a first input terminal 92 and a second input terminal 93.

[0146] The device 91 for controlling wearable devices can be Figure 7 The device 7 in the middle that controls the wearable device can also be used for Figure 8 The device 8 controls the wearable device. The device 91 controlling the wearable device has been described in detail in the above embodiments and will not be further described here. The first input terminal 92 is configured to receive a first voice signal, wherein the first voice signal is a bone conduction signal. The second input terminal 93 is configured to receive a second voice signal, wherein the second voice signal is a non-bone conduction signal.

[0147] In some embodiments, the second input terminal 93 is a microphone with lower received voice signal energy, which is either a directional microphone or an omnidirectional microphone.

[0148] Figure 10 A block diagram of an electronic device according to some embodiments of the present disclosure is shown. The means for controlling the wearable device exists in the form of an electronic device.

[0149] Figure 10 The electronic device 10 shown can be a computer system with a dedicated hardware structure, which can perform corresponding functions when the relevant application is installed.

[0150] Electronic devices include, but are not limited to, mobile terminals such as smartphones, laptops, personal digital assistants (PDAs), tablet computers (PCs), PMPs (portable multimedia players), in-vehicle terminals (such as in-vehicle navigation terminals), wearable devices, and fixed terminals such as digital televisions and desktop computers.

[0151] like Figure 10As shown, the Central Processing Unit (CPU) 101 performs various processes based on programs stored in the Read-Only Memory (ROM) 102 or programs loaded from the storage section 108 into the Random Access Memory (RAM) 103. The RAM 103 stores data required as needed when the CPU 101 performs various processes, etc. The CPU is merely exemplary; it could also be other types of processors, such as the various processors described above. The ROM 102, RAM 103, and storage section 108 can be various forms of computer-readable storage media. It should be noted that although... Figure 10 The image shows ROM 102, RAM 103 and storage section 108, but one or more of them may be combined or located in the same or different memory or storage modules.

[0152] CPU 101, ROM 102 and RAM 103 are interconnected via bus 104. Input / output interface 105 is also connected to bus 104.

[0153] The following components are connected to the input / output interface 105: input section 106, such as a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output section 107, including displays such as cathode ray tube (CRT), liquid crystal display (LCD), speakers, vibrators, etc.; storage section 108, including hard disks, magnetic tapes, etc.; and communication section 109, including network interface cards such as LAN cards, modems, etc. Communication section 109 allows communication processing via a network such as the Internet. It is easy to understand that, although... Figure 10 The portion of the electronic device 10 shown communicates via bus 104, but it may also communicate via a network or other means, wherein the network may include a wireless network, a wired network, and / or any combination of wireless and wired networks.

[0154] As needed, drive 1010 is also connected to input / output interface 105. Removable media 1011, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 1010 as needed, so that computer programs read from them can be installed into storage section 108 as needed.

[0155] When the above series of processes are implemented through software, the program constituting the software can be installed from a network such as the Internet or a storage medium such as a removable medium 1011.

[0156] According to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product that, when run on a computer, causes the computer to perform the methods described in any of the foregoing embodiments. The computer program product includes computer instructions carried on a computer-readable medium, containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer instructions can be downloaded and installed from a network via communication section 109, or installed from storage section 108, or installed from ROM 102. When the computer program is executed by CPU 101, the methods of the embodiments of this disclosure are performed.

[0157] It should be noted that, in the context of this disclosure, a computer-readable medium can be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0158] A computer-readable medium may be a computer-readable storage medium, a computer-readable signal medium, or any combination thereof.

[0159] Computer-readable storage media include, but are not limited to, systems, apparatuses, or devices that are electrical, magnetic, optical, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Computer instructions are stored on the computer-readable storage medium that, when executed by a processor, implement the methods described in any of the foregoing embodiments.

[0160] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0161] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0162] In some embodiments, a computer program is also provided, comprising: instructions that, when executed by a processor, cause the processor to perform the method for controlling a wearable device as described in any of the foregoing embodiments. For example, the instructions may be embodied in computer program code.

[0163] In embodiments of this disclosure, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0164] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0165] The functions described above can be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that can be used include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0166] While specific embodiments of this disclosure have been described in detail by way of example, those skilled in the art should understand that the examples are for illustrative purposes only and not intended to limit the scope of this disclosure. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this disclosure. The scope of this disclosure is defined by the appended claims.

Claims

1. A method for controlling a wearable device, comprising: Acquire a first voice signal received by a first input terminal of a wearable device, wherein the first voice signal is a bone conduction signal; Acquire a second voice signal received at the second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; Determine the correlation between the first speech signal and the second speech signal; and The wearable device is controlled based on the correlation between the first and second voice signals and the second voice signal.

2. The method for controlling a wearable device according to claim 1, wherein, Determining the correlation between the first speech signal and the second speech signal includes: Determine the correlation between a single frame signal of the first speech signal and the corresponding frame signal of the second speech signal at the same time.

3. The method for controlling a wearable device according to claim 2, wherein, The step of controlling the wearable device based on the correlation between the first voice signal and the second voice signal, and the second voice signal, includes: Determine the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than a first threshold; and In response to the number of frames exceeding a second threshold and the second voice signal containing a control instruction, the wearable device is controlled.

4. The method for controlling a wearable device according to claim 3, wherein, The number of the multi-frame signals is determined according to the control delay requirements of the wearable device.

5. The method for controlling a wearable device according to claim 2, further comprising: Based on the correlation between the first speech signal and the second speech signal, the output of the speech content in the second speech signal is controlled.

6. The method for controlling a wearable device according to claim 5, wherein, Based on the correlation between the first speech signal and the second speech signal, controlling the output of the speech content in the second speech signal includes: In response to a third threshold being met by the number of frames in the multi-frame signal of the first speech signal whose correlation with the corresponding frame signal of the second speech signal is greater than a first threshold, the speech content in the second speech signal is output.

7. The method for controlling a wearable device according to claim 6, wherein, The number of the multi-frame signals is determined according to the cloud-based voice recognition latency requirements corresponding to the wearable device.

8. The method for controlling a wearable device according to claim 5, wherein, The time points of the first and last characters in the second speech signal are determined based on the correlation between the first speech signal and the corresponding frame signal of the second speech signal in the multi-frame signal.

9. The method for controlling a wearable device according to claim 8, further comprising: The output of the speech content ends when the time point between the current time point and the last word in the second speech signal is greater than a time threshold.

10. The method for controlling a wearable device according to any one of claims 1 to 9, wherein the second input terminal is a microphone with lower received voice signal energy, either a directional microphone or an omnidirectional microphone.

11. The method for controlling a wearable device according to claim 3, wherein, The control indications include a wake-up indication.

12. The method for controlling a wearable device according to any one of claims 1 to 9, 11, further comprising: Before determining the correlation between the first speech signal and the second speech signal, acoustic echo cancellation processing is performed on the first speech signal and the second speech signal.

13. A device for controlling a wearable device, comprising: The first acquisition module is configured to acquire a first voice signal received by a first input terminal of the wearable device, wherein the first voice signal is a bone conduction signal; The second acquisition module is configured to acquire a second voice signal received by the second input terminal of the wearable device, wherein the second voice signal is a non-bone conduction signal; The correlation determination module is configured to determine the correlation between the first speech signal and the second speech signal; and The control module is configured to control the wearable device based on the correlation between the first voice signal and the second voice signal, and the second voice signal.

14. A device for controlling a wearable device, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute the method of controlling a wearable device as described in any one of claims 1 to 12 based on instructions stored in the memory.

15. A wearable device, comprising: The apparatus for controlling a wearable device as described in claim 13 or 14; A first input terminal is configured to receive a first speech signal, wherein the first speech signal is a bone conduction signal; and The second input terminal is configured to receive a second voice signal, wherein the second voice signal is a non-bone conduction signal.

16. A computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the method of controlling a wearable device as described in any one of claims 1 to 12.

17. A computer program product comprising a computer program or instructions that, when executed by a processor, implement the method for controlling a wearable device as described in any one of claims 1 to 12.

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