METHODS AND APPARATUS FOR DETECTING A VOICE COMMAND

• US 20140274203A1
• Filed: 03/12/2013
• Published: 09/18/2014
• Est. Priority Date: 03/12/2013
• Status: Active Grant

• Current Assignee: Cerence Operating Company (Cerence Inc.)
• Original Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Inventors: Ganong, William F. III, Van Mulbregt, Paul Adrian, Sejnoha, Vladimir, Wilson, Glen
• Granted Patent: US 11,393,461 B2
• Time in Patent Office: Days
• US Class Current: 455/556.1
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command
• CPC Class Codes: G10L 2015/225 Feedback of the input speech
• CPC Class Codes: G10L 2015/226 using non-speech characteristics
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10
• CPC Class Codes: H04M 1/724 User interfaces specially adapted for cordless or mobile telephones
• CPC Class Codes: H04M 2250/74 with voice recognition means voice activated dialling H04M1/271; voice recognition algorithms G10L15/00
• CPC Class Codes: H04W 40/005 Routing actions in the presence of nodes in sleep or doze mode
• CPC Class Codes: H04W 52/0251 using monitoring of local events, e.g. events related to user activity
• CPC Class Codes: H04W 52/0254 detecting a user operation or a tactile contact or a motion of the device
• CPC Class Codes: H04W 52/0261 managing power supply demand, e.g. depending on battery level
• CPC Class Codes: H04W 88/02 Terminal devices
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Claims

1. A method of monitoring an acoustic environment of a mobile device for voice commands when the mobile device is operating in a low power mode, the method comprising:

receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode;

detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode; and

using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

2. The method of claim 1, further comprising transitioning the mobile device from the low power mode to an active mode when it is detected that the acoustic input includes a voice command.

3. The method of claim 1, wherein the at least one contextual cue includes at least one of a time the acoustic input was received, motion of the mobile device, location of the mobile device, occurrence of an event on the mobile device, recent activity on the mobile device, a stored sample of the acoustic environment of the mobile device, and a power source of the mobile device.

4. The method of claim 3, wherein the at least one contextual cue includes the time the acoustic input was received, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on the time the acoustic input was received.

5. The method of claim 3, wherein the at least one contextual cue includes recent activity on the mobile device, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on at least one of how recently the user activated the mobile device, how recently the user issued a voice command and how recently the user performed at least one action on the mobile device.

6. The method of claim 3, wherein the at least one contextual cue includes an occurrence of an event on the mobile device, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on whether the acoustic input is received proximate in time with the occurrence of the event.

7. The method of claim 3, wherein the at least one contextual cue includes motion of the mobile device received as an input from an accelerometer of the mobile device, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on an assessment of whether the user moved the mobile device proximate in time with receiving the acoustic input based, at least in part, on the input from the accelerometer.

8. The method of claim 3, wherein the at least one contextual cue includes the location of the mobile device, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on determining whether the mobile device is located in at least one of a vehicle, a home or a place of work of the user of the mobile device.

9. The method of claim 3, wherein the at least one contextual cue includes the power source of the mobile device, the method further comprising influencing evaluation of at least one of the plurality of processing stages based on at least one of determining whether the mobile device is being powered using the battery or connected to wall power, and a state of the battery if the mobile device is being powered using the battery.

10. The method of claim 3, wherein the at least one contextual cue includes the sample of the acoustic environment obtained by the mobile device by storing acoustic input previously received by the mobile device and determined not to include a voice command, the method further comprising subtracting the sample of the acoustic environment from the acoustic input.

11. The method of claim 1, wherein a sequence of performing the plurality of processing stages is determined, at least in part, by the at least one contextual cue.

12. The method of claim 1, wherein the mobile device includes a primary processor and a secondary processor, and wherein at least one first processing stage of the plurality of processing stages is performed by the secondary processor prior to engaging the primary processor to process the acoustic input.

13. The method of claim 12, wherein at least one second processing stage of the plurality of processing stages is performed by the primary processor only after the at least one first processing stage is performed and neither concludes that the acoustic input includes a voice command nor concludes that the acoustic input is the result of spurious acoustic activity.

14. The method of claim 12, wherein performing the at least one first processing stage includes performing at least one voice activity detection processing stage including performing at least one of spectral analysis on the acoustic input to evaluate whether the spectrum of the acoustic input is indicative of voice activity, periodicity analysis to evaluate whether the signal periodicity is indicative of voice activity, and phone loop analysis to evaluate whether the acoustic input includes speech.

15. The method of claim 12, wherein performing the at least one first processing stage comprises performing limited vocabulary automatic speech recognition on the acoustic input to detect whether the acoustic input includes an explicit voice trigger.

16. The method of claim 12, wherein performing the at least one second processing stage comprises performing at least one speech processing stage including at least one of automatic speech recognition on the acoustic input and at least one natural language processing stage to understand the meaning of the voice command.

17. The method of claim 1, wherein the mobile device is capable of connecting to at least one server via a network, the method further comprising transmitting at least a portion of the acoustic information to the at least one server via the network for processing by the at least one server.

18. The method of claim 1, further comprising performing one or more default actions when a specific task could not be ascertained from the acoustic input.

19. At least one computer readable medium encoded with instructions that, when executed on at least one processor, perform a method of monitoring an acoustic environment of a mobile device to receive acoustic input from the environment of the mobile device while the mobile device is operating in a low power mode, the method comprising:

detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode; and

using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

20. A mobile device comprising:

at least one input to receive acoustic input from an environment of the mobile device while the mobile device is operating in a low power mode;

at least one processor configured to;

detect whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode; and

use at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.