Smart text and voice feedback for voice assistants

Abstract

A method for text feedback includes receiving, by a controller, an utterance from a user; determining, by an automatic speech recognition engine of the controller, a plurality of speech recognition results based on the utterance from the user, wherein the speech recognition results include possible commands; determining, by the automatic speech recognition engine of the controller, a plurality of confidence scores for each of the plurality of speech recognition results; determining, by the controller, a text characteristic for each of a plurality of possible commands from the confidence scores for each of the plurality of speech recognition results; and commanding, by the controller, a display to show text corresponding to each of the plurality of possible commands having the text characteristic determined by the controller.

Description

Technical Field

[0001] introduction This disclosure relates to vehicles, and more particularly to intelligent text and voice feedback systems and methods for vehicle voice assistants. Background Technology

[0002] Some vehicles may include a speech recognition system that can interpret audio received from a user into text fields and intents. Upon receiving speech, the speech recognition system can execute commands based on the speech received from the user. Summary of the Invention

[0003] This disclosure describes a method for providing users with emphasized visual cues in a crowded, centrally stacked display in a vehicle. In some situations, such as during point-of-interest (POI) navigation, address search, contact name phone calls, or hypothesis lists (i.e., speech recognition results), selecting the most appropriate option from a visual display can be challenging and time-consuming. For example, when users are driving, their eyes need to be focused on the road, making the selection of the most appropriate option from a visual display both challenging and time-consuming.

[0004] In this disclosure, the final hypothesis list is merged by incorporating prior information reflecting the most frequent recipients of phone calls / texts, the most previously visited Point of Interest (POI), and nearby POIs or the most frequently used control commands. After generating the final hypothesis list, more probable results are emphasized by calibrating the font size of more likely items. This ergonomically makes it easier for users to select their desired options.

[0005] In one aspect of this disclosure, a method for text feedback includes: receiving utterance from a user by a controller; determining a plurality of speech recognition results by an automatic speech recognition engine of the controller based on the utterance from the user, wherein the speech recognition results are probable commands; determining a plurality of confidence scores for each of the plurality of speech recognition results determined by the automatic speech recognition engine by the controller; determining text features for each of the plurality of probable commands by the controller based on the confidence scores for each of the plurality of speech recognition results; and displaying text corresponding to each of the plurality of probable commands having the text features determined by the controller by a controller command display.

[0006] In this disclosure, the controller determines the size of each of a plurality of possible commands based on a confidence score according to the screen size of the display.

[0007] In this disclosure, the controller determines the magnitude of each of a plurality of possible commands based on a confidence score, according to the number of speech recognition results determined by the controller’s automatic speech recognition engine.

[0008] In this disclosure, the controller determines the size of each of a plurality of possible commands based on a confidence score, calculated as the sum of the confidence scores of the plurality of speech recognition results. The font size of the hypothesis depends on the relative probability of the corresponding result. For example, the confidence score of the first hypothesis may be 8000, and the score of the second hypothesis may be 6400. Therefore, the font size of the second hypothesis should be 80% of that of the first hypothesis.

[0009] In this disclosure, text characteristics include text size, text color, and / or color contrast relative to the background color of the display screen. Font size also depends on the aspect ratio of the display area. For example, this will differ for clusters, center stack module displays, and HUDs. This should also be taken into account in addition to the screen's background color.

[0010] In this disclosure, the method further includes commanding a speaker to provide voice feedback regarding the plurality of speech recognition results in response to determining the plurality of speech recognition results.

[0011] In an aspect of this disclosure, the method further includes determining the audio volume of the voice feedback for each of the plurality of speech recognition results based on the plurality of confidence scores for each of the plurality of speech recognition results determined by an automatic speech recognition engine.

[0012] In this disclosure, the audio volume of the voice feedback of each of the plurality of speech recognition results is determined based on the maximum volume of the speaker and the maximum confidence score.

[0013] This disclosure also describes a control system for a vehicle. In this aspect of the disclosure, the control system includes: a user interface comprising a display and a microphone; and a controller communicating with the user interface. The controller includes an automatic engine recognition system and is programmed to perform the methods described above.

[0014] The present invention also discloses the following technical solutions: 1. A method for text feedback, comprising: The controller receives the user's input. The controller's automatic speech recognition engine determines multiple speech recognition results based on the user's utterance, wherein the speech recognition results include multiple possible commands; and The controller's automatic speech recognition engine determines multiple confidence scores for each of the multiple speech recognition results; The controller determines the textual characteristics of each of the plurality of possible commands based on the confidence score for each of the plurality of speech recognition results; and The controller command display shows the text corresponding to each of a plurality of possible commands having the text characteristics determined by the controller.

[0015] 2. The method according to technical solution 1, wherein the controller determines the size of each of a plurality of possible commands based on the confidence score and the screen size of the display.

[0016] 3. The method according to technical solution 2, wherein the controller determines the magnitude of each of a plurality of possible commands based on the confidence score and the number of speech recognition results determined by the controller's automatic speech recognition engine.

[0017] 4. The method according to technical solution 3, wherein the controller determines the size of each of a plurality of possible commands based on the confidence score and the sum of the confidence scores of the plurality of speech recognition results.

[0018] 5. The method according to technical solution 1, wherein the text characteristic is text size.

[0019] 6. The method according to technical solution 1, wherein the text characteristic is text color.

[0020] 7. The method according to technical solution 1, wherein the text characteristic is the color contrast relative to the background color of the display screen.

[0021] 8. The method according to technical solution 1, further comprising, in response to determining the plurality of speech recognition results, commanding a speaker to provide voice feedback regarding the plurality of speech recognition results.

[0022] 9. The method according to technical solution 8, further comprising determining the audio volume of the voice feedback of each of the plurality of speech recognition results based on the plurality of confidence scores for each of the plurality of speech recognition results determined by the automatic speech recognition engine.

[0023] 10. The method according to technical solution 9, wherein the audio volume of the voice feedback of each of the plurality of speech recognition results is determined based on the maximum volume of the speaker and the maximum confidence score.

[0024] 11. A control system for a vehicle, the control system comprising: The user interface includes a display and a microphone; A controller that communicates with the user interface, wherein the controller includes an automatic recognition engine and is programmed to: Receive messages from users; Multiple speech recognition results are determined based on the utterance from the user, wherein the speech recognition results include multiple possible commands; and Determine multiple confidence scores for each of the plurality of speech recognition results determined by the automatic speech recognition engine of the controller; and The textual characteristics of each of the plurality of possible commands are determined based on the confidence score used for each of the plurality of speech recognition results; The command to the display shows text corresponding to each of a plurality of possible commands having the text characteristics determined by the controller.

[0025] 12. The control system according to technical solution 11, wherein the controller is programmed to determine the size of each of a plurality of possible commands based on the confidence score and the screen size of the display.

[0026] 13. The control system according to technical solution 12, wherein the controller is programmed to determine the magnitude of each of a plurality of possible commands based on the confidence score and the number of speech recognition results determined by the controller's automatic speech recognition engine.

[0027] 14. The control system according to technical solution 13, wherein the controller is programmed to determine the magnitude of each of a plurality of possible commands based on the sum of the confidence scores of the plurality of speech recognition results.

[0028] 15. The control system according to technical solution 11, wherein the text characteristic is text size.

[0029] 16. The control system according to technical solution 11, wherein the text characteristic is text color.

[0030] 17. The control system according to technical solution 11, wherein the text characteristic is a color contrast relative to the background color of the display screen.

[0031] 18. The control system according to technical solution 11, wherein the controller is further programmed to command the speaker to provide voice feedback regarding the plurality of speech recognition results in response to determining the plurality of speech recognition results.

[0032] 19. The control system according to technical solution 18, wherein the controller is further programmed to determine the audio volume of the voice feedback of each of the plurality of speech recognition results based on the plurality of confidence scores for each of the plurality of speech recognition results determined by the automatic speech recognition engine.

[0033] 20. The control system according to technical solution 19, wherein the audio volume of the voice feedback of each of the plurality of speech recognition results is determined based on the maximum volume of the speaker and the maximum confidence score.

[0034] The above features and advantages of this teaching, as well as other features and advantages, will readily become apparent from the following detailed description of some of the best modes and other embodiments for carrying out this teaching as defined in the appended claims when understood in conjunction with the accompanying drawings. Attached Figure Description

[0035] This disclosure will be described in conjunction with the following accompanying drawings, wherein the same reference numerals denote the same elements.

[0036] Figure 1 It is a schematic block diagram of a vehicle.

[0037] Figure 2 This is a diagram of the vehicle's display screen.

[0038] Figure 3 This is a flowchart of a method used for text feedback.

[0039] Figure 4 This is a flowchart of a method used for text feedback. Detailed Implementation

[0040] The following detailed description is merely exemplary in nature and is not intended to limit application or use. Furthermore, it is not intended to be bound by the express or implied theories presented in the foregoing technical field, background art, summary of the invention, or the following detailed description. As used herein, the term "module" refers individually or in combination to hardware, software, firmware, electronic control components, processing logic, and / or processor devices, including but not limited to: application-specific integrated circuits (ASICs), electronic circuits, processors (shared, dedicated, or grouped) and memories executing one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the described functionality.

[0041] Embodiments of this disclosure may be described herein in terms of functional and / or logical block components and various processing steps. It should be understood that such block components may be implemented by a plurality of hardware, software, and / or firmware components configured to perform specified functions. For example, embodiments of this disclosure may employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, etc., which may implement various functions under the control of one or more microprocessors or other control devices. Furthermore, those skilled in the art will understand that embodiments of this disclosure may be practiced in conjunction with several systems, and the systems described herein are merely exemplary embodiments of this disclosure.

[0042] For the sake of brevity, techniques related to signal processing, data fusion, signaling, control, and other functional aspects of the system (and its various operating components) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures included herein are intended to illustrate exemplary functional relationships and / or physical connections between various elements. It should be noted that alternative or additional functional relationships or physical connections may exist in the embodiments of this disclosure.

[0043] like Figure 1 As depicted, vehicle 10 typically includes a chassis 12, a body 14, front wheels, and rear wheels 17, and may be referred to as a vehicle system. In the depicted embodiment, vehicle 10 includes two front wheels 17a and two rear wheels 17b. The body 14 is arranged on the chassis 12 and substantially surrounds the various components of vehicle 10. The body 14 and chassis 12 may together form a frame. Each wheel 17 is rotatably coupled to chassis 12 near a corresponding corner of body 14. Vehicle 10 includes a front axle 19 coupled to the front wheels 17a and a rear axle 25 coupled to the rear wheels 17b.

[0044] In various embodiments, vehicle 10 may be an autonomous vehicle, and control system 98 is integrated into vehicle 10. Control system 98 may be simply referred to as the system. Vehicle 10 is, for example, a vehicle automatically controlled to transport passengers from one location to another. In the illustrated embodiment, vehicle 10 is depicted as a passenger car, but it should be understood that other vehicles may also be used, including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), marine vessels, aircraft, etc. In exemplary embodiments, vehicle 10 is a so-called Level 4 or Level 5 automation system. Level 4 system indicates “high automation,” referring to aspects of dynamic driving tasks performed by an automated driving system in a driving mode-specific manner, even when a human driver does not properly respond to intervention requests. Level 5 system indicates “full automation,” referring to aspects of dynamic driving tasks performed by an automated driving system at all times under several road and environmental conditions that can be managed by a human driver.

[0045] As shown, vehicle 10 typically includes a propulsion system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. In various embodiments, the propulsion system 20 may include an electric motor, such as a traction motor and / or a fuel cell propulsion system. Vehicle 10 further includes a battery (or battery pack) 21 electrically connected to the propulsion system 20. Thus, the battery 21 is configured to store electrical energy and supply electrical energy to the propulsion system 20. Additionally, the propulsion system 20 may include an internal combustion engine. The transmission system 22 is configured to transmit power from the propulsion system 20 to the vehicle wheels 17 according to a selectable speed ratio. According to various embodiments, the transmission system 22 may include a step-ratio automatic transmission, a continuously variable transmission (CVT), or other suitable transmission. The braking system 26 is configured to provide braking torque to the vehicle wheels 17. In various embodiments, the braking system 26 may include friction braking, brake-by-wire braking, regenerative braking systems (such as electric motors), and / or other suitable braking systems. The steering system 24 affects the position of the vehicle wheels 17. Although depicted as including a steering wheel for illustrative purposes, in some embodiments contemplated within the scope of this disclosure, the steering system 24 may not include a steering wheel.

[0046] Sensor system 28 includes one or more sensors 40 (i.e., sensing devices) that sense observable conditions of the external and / or internal environment of vehicle 10. Sensors 40 communicate with controller 34 and may include, but are not limited to, one or more radars, one or more light detection and ranging (LiDAR) sensors, one or more ground-penetrating radar (GPR) sensors, one or more Global Positioning System (GPS) devices, one or more cameras (e.g., optical cameras and / or thermal cameras, such as rear cameras and / or front cameras), speed sensors, steering angle sensors, ultrasonic sensors, one or more inertial measurement units (IMUs), and / or other sensors.

[0047] The actuator system 30 includes one or more actuator devices 42 that control one or more vehicle features, such as, but not limited to, the propulsion system 20, the transmission system 22, the steering system 24, and the braking system 26. In various embodiments, the vehicle features may further include interior and / or exterior vehicle features, such as, but not limited to, doors, trunk, and cabin features, such as ventilation, music, lighting, etc. (not numbered).

[0048] Sensor system 28 includes one or more Global Positioning System (GPS) transceivers configured to detect and monitor route data (i.e., route information). The GPS device is configured to communicate with GPS to locate the position of vehicle 10 on Earth. The GPS device communicates electronically with controller 34. Because sensor system 28 provides data to controller 34, sensor system 28 and its sensors 40 are considered a source of information (or simply a source).

[0049] Data storage device 32 stores data for use in automatically controlling vehicle 10. In various embodiments, data storage device 32 stores a defined map of the navigable environment. In various embodiments, the defined map may be predefined by and obtained from a remote system. For example, the defined map may be assembled by a remote system and transmitted (wirelessly and / or via wired means) to vehicle 10 and stored in data storage device 32. Data storage device 32 may be part of controller 34, separate from controller 34, or part of controller 34 and a separate system.

[0050] The controller 34 includes at least one processor 44 and a non-transitory computer-readable storage device or medium 46. The processor 44 may be a custom or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among several processors associated with the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, a combination thereof, or generally a means for executing instructions. For example, the computer-readable storage device or medium 46 may include volatile and non-volatile storage devices in the form of read-only memory (ROM), random access memory (RAM), and non-deleteable memory (KAM). KAM is a persistent or non-volatile memory that can be used to store various operational variables when the processor 44 is powered off. The computer-readable storage device or medium 46 may be implemented using several memory devices, such as PROM (programmable read-only memory), EPROM (electrical PROM), EEPROM (electrically erasable PROM), flash memory, or another electrical, magnetic, optical, or combined memory device capable of storing data, some of which represents executable instructions used by the controller 34 to control the vehicle 10. The controller 34 is programmed with an automatic speech recognition (ASR) engine.

[0051] The instructions may include one or more separate programs, each of which includes an ordered list of executable instructions for implementing logical functions. When executed by processor 44, the instructions receive and process signals from sensor system 28, perform logic, calculations, methods, and / or algorithms for automatically controlling components of vehicle 10, and generate control signals to actuator system 30 based on the logic, calculations, methods, and / or algorithms to automatically control components of vehicle 10. Although in Figure 1 A single controller 34 is shown, but embodiments of vehicle 10 may include several controllers 34 that communicate via a suitable communication medium or a combination of communication media and cooperate to process sensor signals, execute logic, calculations, methods and / or algorithms, and generate control signals to automatically control the features of vehicle 10.

[0052] In various embodiments, one or more instructions of controller 34 are embodied in control system 98. Vehicle 10 includes user interface 23, which may be a touchscreen in the dashboard. User interface 23 may include, but is not limited to, alarms, such as speakers 27 for providing sound, haptic feedback in vehicle seats or other objects, displays 29, microphones 31, and / or other devices suitable for providing notifications to the vehicle operator of vehicle 10. User interface 23 communicates electronically with controller 34 and is configured to receive input from a user (e.g., a vehicle operator). Therefore, controller 34 is configured to receive input from a user via user interface 23. User interface 23 includes displays 29 configured to display information to a user (e.g., a vehicle operator or passenger) and may include one or more speakers to provide auditable notifications to the vehicle operator. User interface 23 may be a driver information center (DIC) capable of providing information to the vehicle operator of vehicle 10.

[0053] The communication system 36 communicates with the controller 34 and is configured to wirelessly transmit information to and from other entities 48, such as, but not limited to, other vehicles (“V2V” communication), infrastructure (“V2I” communication), remote systems, and / or personal devices. In an exemplary embodiment, the communication system 36 is a wireless communication system configured to communicate via a wireless local area network (WLAN) using the IEEE 802.11 standard or by using cellular data communication. However, additional or alternative communication methods, such as Dedicated Short Range Communication (DSRC) channels, are also contemplated within the scope of this disclosure. A DSRC channel refers to a one-way or two-way short- to medium-range wireless communication channel designed specifically for automotive applications, along with a corresponding set of protocols and standards. Therefore, the communication system 36 may include one or more antennas and / or transceivers for receiving and / or transmitting signals, such as Cooperative Sensing Messages (CSM). The communication system 36 is configured to wirelessly transmit information between vehicle 10 and another vehicle. Further, the communication system 36 is configured to wirelessly transmit information between vehicle 10 and infrastructure or other vehicles.

[0054] refer to Figure 2 The display 29 includes a screen 33 configured to display text 35 with various characteristics, such as text color, text size, and / or color contrast relative to the background color of the screen 33 of the display 29. In this disclosure, the size of the screen 33 is referred to as the screen size.

[0055] refer to Figure 3 Controller 34 ( Figure 1 The system is specifically programmed to execute method 100 for text feedback. Method 100 begins at box 102. At box 102, the user of vehicle 10 utters a command or inquiry (i.e., speech). In other words, the user of vehicle 10 provides a verbal inquiry and / or acoustic utterance to the user interface. The microphone 31 of the user interface 23 then receives the verbal inquiry and / or acoustic utterance and transmits it to the controller 34. Method 100 then proceeds to box 104.

[0056] At box 104, the ASR engine of controller 34 receives and processes verbal queries and / or spoken utterances from the user. Subsequently, the ASR engine of controller 34 determines multiple speech recognition results based on the utterances provided by the user. These speech recognition results may be possible commands and / or possible queries, and may be referred to as hypotheses. Furthermore, at box 104, the ASR engine of controller 34 determines a confidence score for each of the multiple speech recognition results. Method 100 then proceeds to box 106.

[0057] At block 106, controller 34 determines whether the ASR engine has identified multiple possible speech recognition results (i.e., hypotheses) or a single possible speech recognition result (i.e., a single hypothesis). In other words, if controller 34 has determined that only a single possible speech recognition result exists, method 100 proceeds to block 108.

[0058] At box 108, controller 34 instructs user interface 23 to provide verbal feedback to the user (if applicable). This verbal feedback may be provided by speaker 27 of user interface 23 and may verbally ask the user of vehicle 10 whether the single possible voice recognition result is correct. Method 100 then proceeds to boxes 110 and 112.

[0059] At box 110, controller 34 instructs the text-to-speech (TTS) engine to use default TTS settings. These TTS settings may include, but are not limited to, phrase rate, pitch, volume, etc. At box 112, controller 34 receives confirmation from the user via user interface 23 that the single possible speech recognition result is correct. For example, the user may verbally confirm that the single possible speech recognition result is correct, and user interface 23 uses microphone 31 to receive this verbal confirmation. If controller 34 receives confirmation from the user via user interface 23 that the single possible speech recognition result is correct, method 100 proceeds to box 114. At box 114, controller 34 determines that the user request has been fulfilled. However, if the user does not confirm via user interface 23 that the single possible speech recognition result is correct, method 100 returns to box 104.

[0060] Returning to box 106, if controller 34 determines that the ASR engine has determined multiple possible speech recognition results (i.e., hypotheses), method 100 proceeds to box 116. At box 116, controller 34 determines a combined confidence score for each of the multiple possible speech recognition results. To do this, at box 118, controller 34 accesses a database storing prior information. Prior information may include, but is not limited to, navigation information (e.g., frequent points of interest (POIs) or nearby POIs); telephone information (e.g., frequent callers and / or text recipients); and / or control information (such as frequent controls for climate, liftgates, screen brightness, etc.). Using the prior information, controller 34 determines a confidence score for each of the multiple possible speech recognition results determined by the ASR engine. Method 100 then proceeds to boxes 120 and 122. The history and prior information can be used to standardize an initial set of hypotheses, and therefore, after the results are reordered, the font size and color will be appropriately adjusted. For example, for a coffee shop, a user might request Starbucks more often than other chains. Therefore, compared to other assumptions, Starbucks would be the first assumption to be considered to have a larger font and a more pronounced font tone.

[0061] At box 120, controller 34 determines text characteristics, such as text color, text size (i.e., font size), and / or color contrast relative to the background color of screen 33, based on the confidence score of each of a plurality of possible speech recognition results. For example, at box 120, controller 34 adjusts the font size and text color of the text 35 to be displayed by display 29. Furthermore, at box 120, controller 34 commands display 29 to show text corresponding to each of the plurality of possible speech recognition results (e.g., possible commands) having the text characteristics determined by controller 34. For example, as Figure 2 As shown, the higher the confidence score of the speech recognition result, the larger the font size of the text corresponding to that specific speech recognition result will be. Furthermore, the higher the confidence score of the speech recognition result, the greater the color contrast relative to the background color of the display screen will be. As a non-limiting example, the controller 34 can use the following equation to determine the text size for each speech recognition result: in: This is the final adjusted text size; It refers to the screen size; N is the number of speech recognition results; It is the sum of the confidence scores of all speech recognition results; and It is the confidence score of the target result.

[0062] The greater the difference in confidence scores, the greater the difference in text size will appear on the screen. The confidence score is the associated likelihood probability of each speech recognition result. The top result will be a vibrant color and font, such as green and bold. If possible, the top result may have slightly higher contrast. The differences between these hypotheses are measured relative to the Delta confidence score. It is always relative to the top hypothesis. This then guides the relative font size and hue of the hypotheses.

[0063] At box 122, controller 34 adjusts the verbal feedback (if applicable). Verbal feedback is provided via speaker 27 of user interface 23. Therefore, at box 122, controller 34 commands speaker 27 to provide verbal feedback regarding the speech recognition results. The verbal feedback can also be weighted or adjusted based on a confidence score, which is based on standardization across multiple hypotheses. The following equation can be used to determine the audio volume of the verbal feedback based on the confidence score and ambient noise. When information is verbally aloud back to the user, larger fonts are assumed to have more emphasis in the voice prompt. Therefore, in addition to font size and color contrast, the verbal feedback should also be adjusted.

[0064] in: Vaudio is the final adjusted audio volume; It is the confidence score of the target result; It is the maximum value of the returned confidence score; This is the maximum audio volume of the infotainment radio; and It is a coefficient used to compensate for environmental noise.

[0065] The prompt phrases in the voice feedback can change from true certainty to certainty or uncertainty based on the confidence score.

[0066] Method 100 then provides the TTS engine with adapted TTS settings (e.g., phrase rate, tone, and volume). In addition to the rate of speech and emphasis on the highest-scoring items, the timeout period for the voice dialogue should also be adjusted to allow users to respond promptly to voice feedback suggestions. Assume the dialogue can now accommodate a timeout period of 1200 ms instead of 1000 ms.

[0067] refer to Figure 4 The controller 34 is specifically programmed to execute method 200 for text feedback. Method 200 begins at box 202. At box 202, the user of vehicle 10 utters a command or inquiry (i.e., a voice statement). In other words, the user of vehicle 10 provides a voice statement to user interface 23. The microphone 31 of user interface 23 then receives the voice statement and transmits it to the controller 34. Method 200 then proceeds to box 204.

[0068] At box 204, the ASR engine of controller 34 receives and processes the user's voice utterances. The ASR engine of controller 34 then determines the recognized test based on the voice utterances. Method 200 then proceeds to box 206.

[0069] At box 206, controller 34 understands the language of the spoken words to identify the request (i.e., the identified request). Then, method 200 proceeds to box 208. At box 208, controller 34 determines whether the user is attempting to make a call based on the identified request. If the user is attempting to make a call, method 200 proceeds to box 210.

[0070] At box 210, controller 34 determines who the likely recipient of the call (i.e., the call receiver) is based on the identified request. To do this, at box 212, controller 34 accesses a database storing prior information. The prior information includes frequent callers and text receivers. If the call receiver is a frequent caller, method 200 proceeds to box 214.

[0071] At box 214, controller 34 increments the confidence score for that specific identified test. Then, method 200 proceeds to box 216. At box 216, controller 34 stores the confidence score determined in box 214 to obtain a merged confidence score. Then, method 200 proceeds to box 218. At box 218, controller 34 transmits the merged confidence score to the TTS engine for TTS adaptation, and the merged confidence score is used for text adaptation, as described above regarding... Figure 3 As described.

[0072] If it is determined at box 210 that the caller is a new caller (i.e., not a frequent caller), then method 200 proceeds to box 220. At box 220, controller 34 lowers the confidence score of that particular identified test. Then, method 200 proceeds to box 216.

[0073] If controller 43 determines that the user is not attempting a call, method 200 proceeds to block 222. At block 222, controller 34 determines whether the identified request is related to a navigation control command. If the identified request is not related to navigation control, method 200 proceeds to block 224. At block 224, controller 34 determines which control the identified request references. To do this, at block 226, controller 34 accesses a database storing prior information.

[0074] If the request identified at box 222 is related to a navigation control command, method 200 proceeds to box 228. At box 228, controller 34 determines a Point of Interest (POI). Specifically, controller 34 determines that the user wants to reach a specific POI (i.e., the requested POI). To do this, at box 230, controller 34 accesses a database storing prior information. Prior information includes frequent or nearby POIs. If controller 34 determines that the requested POI is a frequent or nearby POI, method 200 proceeds to box 232. In addition to usage history regarding the most frequent POIs, proactive context awareness should also be incorporated. Recent POIs can be highlighted in terms of font, color, and voice feedback.

[0075] At box 232, controller 34 increases the confidence score for that particular identified request. However, if controller 34 determines at box 228 that the requested POI is a new POI, method 200 proceeds to box 234. At box 234, controller 34 decreases the confidence score for that particular identified request. Method 200 then proceeds to box 216. Display 29 may adjust text size and color based on the estimated time of arrival (ETA) and / or distance to the POI.

[0076] The detailed description and accompanying drawings or figures are supporting descriptions of this teaching, but the scope of this teaching is defined only by the claims. While some of the best modes and other embodiments for carrying out this teaching have been described in detail, various alternative designs and embodiments exist for practicing this teaching as defined in the appended claims.

Claims

1. A method for text feedback, comprising: The controller receives the user's input. The controller's automatic speech recognition engine determines multiple speech recognition results based on the user's utterance, wherein the speech recognition results include multiple possible commands; and The controller's automatic speech recognition engine determines multiple confidence scores for each of the multiple speech recognition results; The controller determines the textual characteristics of each of the plurality of possible commands based on the confidence score for each of the plurality of speech recognition results; and The controller commands the display to show the text corresponding to each of a plurality of possible commands having the text characteristics determined by the controller, wherein the controller determines the size of the text of each of the plurality of possible commands based on the confidence score and the screen size of the display.

2. The method according to claim 1, wherein, The controller determines the text size of each of a plurality of possible commands based on the confidence score and the number of speech recognition results determined by the controller's automatic speech recognition engine.

3. The method according to claim 2, wherein, The controller determines the magnitude of each of a plurality of possible commands based on the sum of the confidence scores of the plurality of speech recognition results.

4. The method according to claim 1, wherein, The text characteristic mentioned is text size.

5. The method according to claim 1, wherein, The text characteristic mentioned is text color.

6. The method according to claim 1, wherein, The text characteristic is the color contrast relative to the background color of the display screen.

7. The method of claim 1, further comprising, in response to determining the plurality of speech recognition results, commanding a speaker to provide voice feedback regarding the plurality of speech recognition results.

8. The method of claim 7, further comprising determining the audio volume of the voice feedback for each of the plurality of speech recognition results based on the plurality of confidence scores determined by the automatic speech recognition engine for each of the plurality of speech recognition results.

9. The method according to claim 8, wherein, The audio volume of the voice feedback for each of the plurality of speech recognition results is determined based on the maximum volume of the speaker and the maximum confidence score.

10. A control system for a vehicle, the control system comprising: The user interface includes a display and a microphone; A controller that communicates with the user interface, wherein the controller includes an automatic recognition engine and is programmed to: Receive messages from users; Multiple speech recognition results are determined based on the utterance from the user, wherein the speech recognition results include multiple possible commands; and Determine multiple confidence scores for each of the plurality of speech recognition results, determined by the controller's automatic speech recognition engine; and The textual characteristics of each of the plurality of possible commands are determined based on the confidence score used for each of the plurality of speech recognition results; The display is commanded to show text corresponding to each of a plurality of possible commands having text characteristics determined by the controller, wherein the controller is programmed to determine the size of the text of each of the plurality of possible commands based on the confidence score and the screen size of the display.

11. The control system according to claim 10, wherein, The controller is programmed to determine the text size of each of a plurality of possible commands based on the confidence score and the number of speech recognition results determined by the controller's automatic speech recognition engine.

12. The control system according to claim 11, wherein, The controller is programmed to determine the magnitude of each of a plurality of possible commands based on the sum of the confidence scores of the plurality of speech recognition results.

13. The control system according to claim 10, wherein, The text characteristic mentioned is text size.

14. The control system according to claim 10, wherein, The text characteristic mentioned is text color.

15. The control system according to claim 10, wherein, The text characteristic is the color contrast relative to the background color of the display screen.

16. The control system according to claim 10, wherein, The controller is further programmed to command the speaker to provide voice feedback about the plurality of speech recognition results in response to determining the plurality of speech recognition results.

17. The control system according to claim 16, wherein, The controller is further programmed to determine the audio volume of the voice feedback for each of the plurality of speech recognition results based on the plurality of confidence scores determined by the automatic speech recognition engine for each of the plurality of speech recognition results.

18. The control system according to claim 17, wherein, The audio volume of the voice feedback for each of the plurality of speech recognition results is determined based on the maximum volume of the speaker and the maximum confidence score.

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