Audio Data Spread Spectrum Embedding and Detection

• US 20140111701A1
• Filed: 10/15/2013
• Published: 04/24/2014
• Est. Priority Date: 10/23/2012
• Status: Abandoned Application

• Current Assignee: Dolby Laboratories Licensing Corporation (Dolby Laboratories Incorporated)
• Original Assignee: Dolby Laboratories Licensing Corporation (Dolby Laboratories Incorporated)
• Inventors: Radhakrishnan, Regunathan
• Application Number:
  US14/054,438
• Publication Number:
  US 20140111701A1
• Time in Patent Office: Days
• US Class Current: 348/738
• CPC Class Codes: G10L 19/018 Audio watermarking, i.e. embedding inaudible data in the audio signal
• CPC Class Codes: H04N 21/233 Processing of audio elementary streams monitoring, identification or recognition of audio in broadcast systems H04H60/58
• CPC Class Codes: H04N 21/4394 involving operations for analysing the audio stream, e.g. detecting features or characteristics in audio streams arrangements characterised by components specially adapted for monitoring, identification or recognition of audio in broadcast systems H04H60/58
• CPC Class Codes: H04N 21/8358 involving watermark protecting executable software by watermarking G06F21/16; image watermarking in general G06T1/0021; watermarks inserted in still images for transmission purposes H04N1/32144; inserting watermarks during video coding H04N19/467
• CPC Class Codes: H04N 5/602 for digital sound signals

Abstract

An audio data spread spectrum embedding and detection method is presented. For each audio frame, a noise sequence is chosen according to the data to be embedded. Then, a spectrum of a chosen noise sequence is shaped by a spectrum of a current audio frame and subtracted from a current frame'"'"'s spectrum. During detection, a detector is used on a watermarked audio frame to first whiten the watermarked audio frame. Detection scores are then computed against two competing Adaboost learning models. A detected bit is chosen according to the model with a maximum detection score.

Claims

1. A method to embed data in an audio signal, comprising:

selecting a pseudo-random sequence according to desired data to be embedded in the audio signal;

shaping a frequency spectrum of the pseudo-random sequence with a frequency spectrum of the audio signal, thus forming a shaped frequency spectrum of the pseudo-random noise sequence; and

subtracting the shaped frequency spectrum of the pseudo-random sequence from the frequency spectrum of the audio signal spectrum.

2. The method according to claim 1, wherein the selected pseudo-random sequence is a function of pseudo-random chip sequences of {+1, −

1}.

3. The method according to claim 1, wherein the shaping and subtracting steps occur on an audio frame by audio frame basis.

4. The method according to claim 1, wherein the frequency spectrum of the pseudo-random sequence comprises of frequency coefficients different from zero only in a desired frequency range.

5. The method according to claim 4, wherein the desired frequency range is between 2 kHz to 7.5 kHz.

6. The method according to claim 3, wherein the selecting, shaping and subtracting steps for a specific data are repeated for a set number of audio frames.

7. The method according to claim 6, wherein the set number of audio frames is three audio frames.

16. An audio signal receiving arrangement comprising a first device and a second device, the first device comprising an audio watermark embedder to embed a watermark in the audio signal, the second device comprising an audio watermark detector to detect the watermark embedded in the audio signal and adapt processing on the second device according to the extracted watermark data, the audio watermark embedder being operative to embed the watermark in the audio signal according to the method of claim 1, the audio watermark detector being operative to detect the watermark embedded in the audio signal according to the method of claim 8.

17. The audio signal receiving arrangement of claim 16, wherein the first device is a set top box, and the second device is an audio video receiver separate from the set top box.

18. The audio signal receiving arrangement of claim 16, wherein the first device is a first audio video receiver, and the second device is a second audio video receiver separate from the first audio video receiver.

19. An audio signal receiving product comprising a computer system having an executable program executable to implement a first process and a second process, the first process embedding a watermark in the audio signal, the second process detecting the watermark embedded in the audio signal, the second process being adapted according to the detected watermark data, the first process operating according to the method of claim 1, the second process operating according to the method of claim 8.

8. A computer-readable storage medium having stored thereon computer-executable instructions executable by a processor to detect embedded data in an audio signal, the detecting comprising:

calculating detection scores from a set of competing statistical learning models, wherein the detection scores are based on the audio signal; and

performing a detection decision as to which data is embedded in the audio signal by comparing with each other the calculated detection scores.

9. The method according to claim 8, wherein the competing statistical learning models are a statistical learning model for detecting a zero bit and a statistical learning model for detecting a one bit.

10. The method according to claim 8, wherein the competing statistical learning models are Adaboost models.

11. The method according to claim 8, wherein calculating the detection scores comprises obtaining a feature vector from the audio signal.

12. The method according to claim 11, wherein the feature vector is a whitened spectrum of the audio signal.

13. The method according to claim 8, wherein parameters of the statistical learning models are obtained from a computer-based offline training step.

14. The method of claim 13, wherein the offline training step further comprises at least the following two sets of audio data:

a first set of audio data with a same embedded data bit; and

a second set of audio data without any embedded data bit.

15. The method according to claim 14, wherein the off-line training step extracts features from the two sets of audio data and learns the parameters of the statistical learning models.

20. A system to embed data in an audio signal, the system comprising:

a processor configured to;

select a pseudo-random sequence according to desired data to be embedded in the audio signal;

shape a frequency spectrum of the pseudo-random sequence with a frequency spectrum of the audio signal, thus forming a shaped frequency spectrum of the pseudo-random sequence; and

subtract the shaped frequency spectrum of the pseudo-random noise sequence from the frequency spectrum of the audio signal spectrum.

21. The system according to claim 20, wherein the selected pseudo-random sequence is a function of pseudo-random chip sequences of {+1, −

1}.

22. The system according to claim 21, further comprising:

a memory for storing computer-executable instructions accessible by said processor for embedding the data in the audio signal; and

an input/output device configured to, at least, receive the audio signal and provide the audio signal to the processor.

23. A system to detect embedded data in an audio signal, the system comprising:

a processor configured to;

calculating detection scores from a set of competing statistical learning models, wherein the detection scores are based on the audio signal; and

performing a detection decision as to which data is embedded in the audio signal by comparing a first model score for detecting a zero bit with a second model score for detecting a one bit.