SYSTEM AND METHOD FOR GENERATING CLOSED CAPTIONS

• US 20070118373A1
• Filed: 10/05/2006
• Published: 05/24/2007
• Est. Priority Date: 11/23/2005
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Chai, Wei, Lizzi, John, Zinser, Richard, Goldfarb, Helena, Hoebel, Louis, Wise, Gerald, Abraham, Anil
• Application Number:
  US11/538,936
• Publication Number:
  US 20070118373A1
• Time in Patent Office: Days
• US Class Current: 704/235
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 21/06 Transformation of speech into a non-audible representation, e.g. speech visualisation or speech processing for tactile aids G10L15/26 takes precedence

Abstract

A system for generating closed captions from an audio signal includes an audio pre-processor configured to correct one or more predetermined undesirable attributes from an audio signal and to output one or more speech segments. The system also includes a speech recognition module configured to generate from the one or more speech segments one or more text transcripts and a post processor configured to provide at least one pre-selected modification to the text transcripts. Further included is an encoder configured to broadcast modified text transcripts corresponding to the speech segments as closed captions.

Claims

1. A system for generating closed captions from an audio signal, the system comprising:

an audio pre-processor configured to correct one or more predetermined undesirable attributes from an audio signal and to output one or more speech segments;

a speech recognition module configured to generate from the one or more speech segments one or more modified text transcripts;

a post processor configured to provide at least one pre-selected modification to the text transcripts; and

an encoder configured to broadcast modified text transcripts corresponding to the speech segments as closed captions.

2. The system of claim 1, further comprising a configuration manager in communication with the audio pre-processor, the speech recognition module, and the post processor and configured to perform at least one of dynamic system configuration, system initialization, and system shutdown.

3. The system of claim 2, further comprising a voice identification module configured to analyze acoustic features corresponding to the speech segments to identify one or more specific speakers associated with the speech segments, the voice identification module being in communication with the pre-processor and the configuration manager and wherein the configuration manager provides an appropriate individual speaker model for use by the speech recognition module based on input from the voice identification module.

4. The system of claim 2, further comprising one or more language models and wherein the configuration manager communicates with the language models and the post processor for analyzing the text transcripts and applying the appropriate language model.

5. The system of claim 4, wherein the one or more language models comprise at least one of weather, traffic and general news.

6. The system of claim 1, wherein the one or more predetermined undesirable attributes corrected by the audio pre-processor comprises at least one of breath identification, zero level elimination, voice activity detection and crosstalk elimination.

7. The system of claim 6, wherein breath identification comprises attenuation of breaths in the audio signal and extension of the breaths determined to be less than a time interval set by the speech recognition module.

8. The system of claim 6, wherein zero level elimination comprises addition of background noise.

9. The system of claim 6, wherein voice activity detection comprises a filter for removing non-speech portions of the audio signal.

10. The system of claim 6, wherein crosstalk elimination comprises a filter for removing speakers other than a speaker of interest in the audio signal.

11. The system of claim 1, wherein the at least one pre-selected modification to the text transcripts provided by the post processor comprises at least one of context, error correction, vulgarity cleansing, and smoothing and interleaving of captions.

12. The system of claim 11, further comprising one or more context-based models in communication with the post processor and configured to identify an appropriate context associated with the text transcripts and wherein the configuration manager connects an appropriate language model based on an associated context identified by the context-based models.

13. The system of claim 11, wherein error correction comprises word error correction.

14. The system of claim 11, wherein the smoothing and interleaving of captions comprises sending text to the encoder in a timely manner while ensuring that the segments of text corresponding to each speaker are displayed in an order that matches or preserves the order actually spoken by the speakers.

15. The system of claim 12, wherein the context-based models include one or more topic-specific databases for identifying an appropriate context associated with the text transcripts.

16. The system of claim 12, wherein the context-based models are adapted to identify the appropriate context based on a topic specific word probability count in the text transcripts corresponding to the speech segments.

17. The system of claim 1, wherein the speech recognition module is coupled to a training module, wherein the training module is configured to augment dictionaries and language models for one or more speakers by analyzing actual transcripts and building additional speech recognition and voice identification models.

18. The system of claim 17, wherein the training module is configured to manage acoustic and language models used by the speech recognition engine and voice identification models used by the voice identification engine.

19. A method of generating closed captions from an audio signal, the method comprising:

correcting one or more predetermined undesirable attributes from the audio signal and outputting one or more speech segments;

generating from the one or more speech segments one or more text transcripts;

providing at least one pre-selected modification to the text transcripts; and

broadcasting modified text transcripts corresponding to the speech segments as closed captions.

20. The method of claim 19, further comprising performing real-time system configuration.

21. The method of claim 19, further comprising:

identifying one or more specific speakers associated with the speech segments; and

providing an appropriate individual speaker model.

22. The method of claim 19, wherein the one or more predetermined undesirable attributes comprises at least one of breath identification, zero level elimination, voice activity detection and crosstalk elimination.

23. The system of claim 19, wherein the at least one pre-selected modification to the text transcripts comprises at least one of context, error correction, vulgarity cleansing, and smoothing and interleaving of captions.