Speech Signal Similarity

• US 20120059656A1
• Filed: 08/30/2011
• Published: 03/08/2012
• Est. Priority Date: 09/02/2010
• Status: Active Grant

• Current Assignee: Nexidia Incorporated (Nice Ltd)
• Original Assignee: Nexidia Incorporated (Nice Ltd)
• Inventors: Arrowood, Jon A., Lanham, Drew, Gavalda, Marsal, Garland, Jacob B.
• Granted Patent: US 8,670,983 B2
• Time in Patent Office: Days
• US Class Current: 704/254
• CPC Class Codes: G10L 25/00 Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 muting semiconductor-based amplifiers when some special characteristics of a signal are sensed by a speech detector, e.g. sensing when no signal is present, H03G3/34

Abstract

A method for determining a similarity between a first audio source and a second audio source includes: for the first audio source, determining a first frequency of occurrence for each of a plurality of phoneme sequences and determining a first weighted frequency for each of the plurality of phoneme sequences based on the first frequency of occurrence for the phoneme sequence; for the second audio source, determining a second frequency of occurrence for each of a plurality of phoneme sequences and determining a second weighted frequency for each of the plurality of phoneme sequences based on the second frequency of occurrence for the phoneme sequence; comparing the first weighted frequency for each phoneme sequence with the second weighted frequency for the corresponding phoneme sequence; and generating a similarity score representative of a similarity between the first audio source and the second audio source based on the results of the comparing.

Claims

1. A method for determining a similarity between a first audio source and a second audio source, the method comprising:

for the first audio source, performing the steps of;

determining, using an analysis module of a computer, a first frequency of occurrence for each of a plurality of phoneme sequences in the first audio source;

determining, using the analysis module, a first weighted frequency for each of the plurality of phoneme sequences based on the first frequency of occurrence for the phoneme sequence;

for the second audio source, performing the steps of;

determining, using the analysis module, a second frequency of occurrence for each of a plurality of phoneme sequences in the second audio source;

determining, using the analysis module, a second weighted frequency for each of the plurality of phoneme sequences based on the second frequency of occurrence for the phoneme sequence;

comparing, using a comparison module of a computer, the first weighted frequency for each phoneme sequence with the second weighted frequency for the corresponding phoneme sequence; and

generating, using the comparison module, a similarity score representative of a similarity between the first audio source and the second audio source based on the results of the comparing.

2. The method of claim 1, wherein determining the first frequency of occurrence includes, for each phoneme sequence, determining a ratio between a number of times the phoneme sequence occurs in the first audio source and a duration of the first audio source.

3. The method of claim 1, wherein the first weighted frequencies for each first portion of audio are collectively represented by a first vector and the second weighted frequencies for each second portion of audio are collectively represented by a second vector.

4. The method of claim 3, wherein the step of comparing includes determining a cosine of an angle between the first vector and the second vector.

5. The method of claim 1, wherein the step of comparing includes using a latent semantic analysis technique.

6. The method of claim 1, wherein the first audio source forms a part of a first audio file and the second audio source forms a part of a second audio file.

7. The method of claim 1, wherein the first audio source is a first segment of an audio file and the second audio source is a second segment of the audio file.

8. The method of claim 1, further comprising selecting the plurality of phoneme sequences.

9. The method of claim 8, wherein the plurality of phoneme sequences are selected on the basis of a language of at least one of the first audio source and the second audio source.

10. The method of claim 1, wherein each phoneme sequence includes three phonemes.

11. The method of claim 1, wherein each phoneme sequence includes a plurality of words.

12. The method of claim 11, further comprising determining a relevance score for each word in the first audio source.

13. The method of claim 12, wherein the relevance score for each word is determined based on a frequency of occurrence of the word in the first audio source.

14. A method for determining a similarity between a first audio source and a second audio source, the method comprising:

generating, using a computer, a phonetic transcript of the first audio source, the phonetic transcript including a list of phonemes occurring in the first audio source;

searching the second audio source for each phoneme included in the phonetic transcript using the computer;

generating, using the computer, an overall search result for the second audio source, the overall search result including results from the searching; and

generating, using the computer, a score representative of a similarity between the first audio source and the second audio source, the score based on the overall search result.

15. The method of claim 14, wherein the phonetic transcript includes a sequential list of phonemes occurring in the first audio source.

16. A method comprising:

comparing an audio track of a first multimedia source with an audio track of a second multimedia source, the second multimedia source being associated with text content corresponding to closed captioning;

determining a similarity score representative of a similarity between the audio track of the first multimedia source and the audio track of the second multimedia source based on the results of the comparing; and

associating at least some of the text content corresponding to the closed captioning with the first multimedia source if the determined similarity score exceeds a predefined threshold.

17. The method of claim 16, wherein associating at least some of the text content includes:

extracting text content including the closed captioning from the second multimedia source.

18. A method comprising:

processing signals received over a plurality of channels, each channel being associated with a distinct one of a set of geographically dispersed antennas, to determine a similarity score representative of a similarity between pairs of the received signals; and

for each pair of the received signals having a determined similarity score that exceeds a predefined threshold, determining whether the received signals of the pair are time aligned, and if so, removing from further processing one of the received signals of the pair.

19. The method of claim 18, wherein at least some of the received signals correspond to distress calls, and wherein the signals are processed at a computing system in electronic communication with an emergency response provider.