System and method for increasing transmission bandwidth efficiency (“EBT2”)

• US 10,096,326 B2
• Filed: 09/15/2017
• Issued: 10/09/2018
• Est. Priority Date: 09/26/2011
• Status: Active Grant

• Current Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Original Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Inventors: Marko, Paul, Sinha, Deepen, Aggrawal, Hariom
• Primary Examiner(s): Leland, III, Edwin S
• Application Number:
  US15/706,079
• Publication Number:
  US 20180068665A1
• Time in Patent Office: 389 Days
• Field of Search: 704500
• CPC Class Codes: G10L 19/00 Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis in musical instruments G10H
• CPC Class Codes: G10L 19/008 Multichannel audio signal coding or decoding using interchannel correlation to reduce redundancy, e.g. joint-stereo, intensity-coding or matrixing
• CPC Class Codes: G10L 19/0212 using orthogonal transformation
• CPC Class Codes: G10L 2019/0001 Codebooks
• CPC Class Codes: H04H 2201/18 in band on channel [IBOC]
• CPC Class Codes: H04H 60/58 of audio determination or detection of speech characteristics in general G10L25/00; speech recognition in general G10L15/00

Abstract

Systems and methods for increasing transmission bandwidth efficiency by the analysis and synthesis of the ultimate components of transmitted content are presented. To implement such a system, a dictionary or database of elemental codewords can be generated from a set of audio clips. Using such a database, a given arbitrary song or other audio file can be expressed as a series of such codewords, where each given codeword in the series is a compressed audio packet that can be used as is, or, for example, can be tagged to be modified to better match the corresponding portion of the original audio file. Each codeword in the database has an index number or unique identifier. For a relatively small number of bits used in a unique ID, e.g. 27-30, several hundreds of millions of codewords can be uniquely identified. By providing the database of codewords to receivers of a broadcast or content delivery system in advance, instead of broadcasting or streaming the actual compressed audio signal, all that need be transmitted is the series of identifiers along with any modification instructions to the identified codewords. After reception, intelligence on the receiver having access to a locally stored copy of the dictionary can reconstruct the original audio clip by accessing the codewords via the received IDs, modify them as instructed by the modification instructions, further modify the codewords either individually or in groups using the audio profile of the original audio file (also sent by the encoder) and play back a generated sequence of phase corrected codewords and modified codewords as instructed. In exemplary embodiments of the present invention, such modification can extend into neighboring codewords, and can utilize either or both (i) cross correlation based time alignment and (ii) phase continuity between harmonics, to achieve higher fidelity to the original audio clip.

Claims

1. A method comprising:

receiving an audio signal comprising a sequence of unique identifiers to compressed packets with associated modification instructions in a database;

for each identifier in the sequence;

obtaining the compressed packet from the database identified by the identifier,

obtaining the modification instructions associated with the identifier in the sequence, and

modifying the compressed packet according to said modification instructions;

generating a sequence of the modified compressed packets; and

generating an audio output from the generated sequence of the modified compressed packets.

2. The method of claim 1, wherein said modification instructions include results of harmonic analysis and time domain cross-correlation.

3. The method of claim 1, wherein said obtain the modification instructions includes determining if a harmonic flag has been set.

4. The method of claim 3, wherein:

if a harmonic flag has been set, determining a phase in the frequency domain and performing an inverse Odd Discrete Frequency Transform (ODFT); and

if no harmonic flag has been set, performing time domain data shifting.

5. The method of claim 4, further comprising performing Root Mean Square (RMS) correction followed by combining neighboring frames using an adaptive window.

6. The method of claim 1, wherein said modification instructions include performing a linear or non-linear transformation on the identified compressed packet.

7. The method of claim 1, wherein said modification instructions include performing a linear or non-linear transformation on the identified compressed packet and neighboring compressed packets.

8. The method of claim 1, wherein each unique identifier is a unique identification number comprising approximately 20-30 bits.

9. The method of claim 1, wherein each of the compressed audio packets in the database is generated based at least in part on:

sampling a first audio clip;

dividing the audio clip into a plurality of RMS normalized time domain segments; and

performing an ODFT for each RMS normalized time domain segment.

10. The method of claim 9, wherein each of the compressed audio packets in the database is generated based at least further in part on:

performing psychoacoustic analysis over each segment to calculate masking thresholds corresponding to N quality indices.

11. The method of claim 9, wherein each of the compressed audio packets in the database is generated based at least further in part on:

analyzing each segment present in the database to identify a uniqueness of the segment in comparison to other segments in the database;

removing, based on a predefined metric, any segment that is not unique; and

storing the unique segments in the database as the compressed packets.

12. The method of claim 11, wherein the predefined metric comprises a similarity score based on at least 20 similarity gradations.

13. The method of claim 11, wherein each of the compressed audio packets in the database is generated based at least further in part on:

after the storing the unique segments of the first audio clip, comparing the unique segments in the database with other segments associated with a second audio clip; and

removing, based on the predefined metric, one or more unique segments of the first audio clip that are similar to one or more segments associated with the second audio clip.

14. The method of claim 12, wherein the similarity score is a number between 1-5, with increments every 0.1 and with 1 being the most similar.

15. The method of claim 14, wherein compressed packets being determined to be similar is based on a similarity score between approximately 1-1.4.