System for suppressing rain noise

• US 8,374,855 B2
• Filed: 05/19/2011
• Issued: 02/12/2013
• Est. Priority Date: 02/21/2003
• Status: Expired due to Term

• Current Assignee: Malikie Innovations Limited (Key Patent Innovations Limited)
• Original Assignee: QNX Software Systems Limited (Canada) (Blackberry Limited)
• Inventors: Hetherington, Phillip A., Groves, Adrian R.
• Primary Examiner(s): Opsasnick, Michael N
• Application Number:
  US13/111,274
• Publication Number:
  US 20110282660A1
• Time in Patent Office: 635 Days
• Field of Search: 704/226
• US Class Current: 704/226
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 21/0232 Processing in the frequency domain

Abstract

A voice enhancement logic improves the perceptual quality of a processed signal. The voice enhancement system includes a noise detector and a noise attenuator. The noise detector detects and models the noise associated with rain. The noise attenuator dampens or reduces the rain noise from a signal to improve the intelligibility of an unvoiced, a fully voiced, or a mixed voice segment.

Claims

1. A system for attenuating rain noise, comprising:

a rain noise detector configured to analyze a frequency spectrum of an input signal to identify whether the input signal contains a rain noise, where the rain noise detector is configured to fit a model to a portion of the input signal and identify that a noise of the input signal is associated with rain based on a correlation between the model and the portion of the input signal; and

a rain noise attenuator configured to remove at least a portion of the rain noise identified by the noise detector from the input signal to obtain an output sound signal with reduced rain noise content.

2. The system of claim 1, where the model comprises a best-fit regression line.

3. The system of claim 2, where the rain noise detector is configured to derive a correlation between the best-fit regression line and the portion of the input signal, and identify whether the input signal contains the rain noise based on the correlation.

4. The system of claim 1, where the rain noise detector is configured to separate a noise segment from a remaining portion of the input signal, and analyze the noise segment to detect an occurrence of rain noise.

5. The system of claim 1, where the rain noise detector is configured to model a spectrum of an identified rain noise, and retain the modeled spectrum of the identified rain noise in memory.

6. The system of claim 1, where the rain noise detector is configured to distinguish between rain and non-rain signal portions based on a continuity measurement of a magnitude or phase of the input signal across multiple frequency bins.

7. The system of claim 1, where the rain noise detector is configured to communicate with a windshield wiper controller of a vehicle, and where the rain noise detector is configured to enable rain noise detection analysis based on information from the windshield wiper controller regarding a state of windshield wipers of the vehicle.

8. The system of claim 1, where the rain noise detector is configured to identify the rain noise based on a rain drop model;

where the rain noise detector is configured to communicate with a windshield wiper controller of a vehicle, and where the rain noise detector is configured to adjust a parameter of the rain drop model based on information from the windshield wiper controller regarding a speed of windshield wipers of the vehicle.

9. The system of claim 1, where the rain noise detector is configured to communicate with a windshield wiper controller of a vehicle, where the rain noise detector is configured to calculate rain intensity or rain drop spacing information by analyzing sound content of the input signal, and where the rain noise detector is configured to transmit the rain intensity or rain drop spacing information to the windshield wiper controller.

10. A method of dampening rain noise, comprising:

fitting a model to a portion of an input signal;

identifying that a noise of the input signal is associated with rain based on a correlation between the model and the portion of the input signal; and

dampening at least a portion of the noise associated with rain from the input signal to obtain an output sound signal with reduced rain noise content.

11. The method of claim 10, where the model comprises a best-fit regression line.

12. The method of claim 10, further comprising:

measuring a continuity of a magnitude or phase of the input signal across multiple frequency bins; and

distinguishing between rain and non-rain signal portions based on the continuity measurement.

13. The method of claim 10, further comprising enabling rain noise detection analysis based on information received from a windshield wiper controller regarding a state of windshield wipers of the vehicle.

14. The method of claim 10, further comprising adjusting a parameter of a rain drop model based on information received from a windshield wiper controller regarding a speed of windshield wipers of the vehicle.

15. The method of claim 10, further comprising:

calculating rain intensity or rain drop spacing information by analyzing sound content of the input signal; and

transmitting the rain intensity or rain drop spacing information to the windshield wiper controller.

16. The method of claim 10, where the act of identifying comprises identifying, by a processor, that the noise of the input signal is associated with rain.

17. A non-transitory computer-readable storage medium with executable instructions stored thereon, where the instructions are configured to cause a processor to perform the steps of:

fitting a model to a portion of an input signal;

identifying that a noise of the input signal is associated with rain based on a correlation between the model and the portion of the input signal; and

dampening at least a portion of the noise associated with rain from the input signal to obtain an output sound signal with reduced rain noise content.

18. The non-transitory computer-readable storage medium of claim 17, where the model comprises a best-fit regression line.

19. The non-transitory computer-readable storage medium of claim 17, where the instructions are further configured to cause the processor to perform the steps of:

measuring a continuity of a magnitude or phase of the input signal across multiple frequency bins; and

distinguishing between rain and non-rain signal portions based on the continuity measurement.