System and method for generating closed captions

• US 20070118372A1
• Filed: 11/23/2005
• 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, Goldfarb, Helena, Hoebel, Louis, Wise, Gerald, Lizzi, John, Abraham, Anil
• Application Number:
  US11/287,556
• Publication Number:
  US 20070118372A1
• 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 is provided. The system includes a speech recognition engine configured to generate one or more text transcripts corresponding to one or more speech segments from an audio signal. The system further includes a processing engine, one or more context-based models and an encoder. The processing engine is configured to process the text transcripts. The context-based models are configured to identify an appropriate context associated with the text transcripts. The encoder is configured to broadcast the text transcripts corresponding to the speech segments as closed captions.

Claims

1. A system for generating closed captions, the system comprising:

a speech recognition engine configured to generate from an audio signal one or more text transcripts corresponding to one or more speech segments;

one or more context-based models configured to identify an appropriate context associated with the text transcripts;

a processing engine configured to process the text transcripts; and

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

2. The system of claim 1, further comprising a voice identification engine coupled to the one or more context-based models, wherein the voice identification engine is configured to analyze acoustic features corresponding to the speech segments to identify specific speakers associated with the speech segments

3. The system of claim 2, wherein the voice identification engine is further configured to filter the speech segments to identify a particular speaker associated with a particular speech segment.

4. The system of claim 1, wherein the processing engine is adapted to analyze the text transcripts corresponding to the speech segments for word errors.

5. The system of claim 4, wherein the processing engine includes a natural language module for analyzing the text transcripts.

6. The system of claim 1, wherein the context-based models include one or more topic-specific databases for identifying an appropriate context associated with the text transcripts.

7. The system of claim 6, 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.

8. The system of claim 1, wherein the speech recognition engine is coupled to a training module, wherein the training module is configured to augment dictionaries and language models for speakers by analyzing actual transcripts and build new speech recognition and voice identification models for new speakers.

9. The system of claim 8, wherein the training module is configured to manage acoustic and language models used by the speech recognition engine.

10. A method for automatically generating closed captioning text, the method comprising:

obtaining one or more speech segments from an audio signal;

generating one or more text transcripts corresponding to the one or more speech segments;

identifying an appropriate context associated with the text transcripts;

processing the one or more text transcripts; and

broadcasting the text transcripts corresponding to the speech segments as closed captioning text.

11. The method of claim 10, comprising analyzing acoustic features corresponding to the speech segments to identify specific speakers associated with the speech segments.

12. The method of claim 11, comprising applying a filtering operation to the speech segments to identify a particular speaker associated with a particular speech segment.

13. The method of claim 10, wherein processing one or more text transcripts comprises analyzing the text transcripts for word errors.

14. The method of claim 13, wherein the analyzing the text transcripts is performed using a natural language technique.

15. The method of claim 10, wherein the identifying an appropriate context comprises utilizing one or more topic specific databases.

16. The method of claim 15, wherein the identifying an appropriate context is based on a topic specific word probability count in the text transcripts corresponding to the speech segments.

17. The method of claim 10, comprising augmenting dictionaries and language models for speakers by analyzing actual transcripts and building new speech recognition and voice identification models for new speakers.

18. The method of claim 17, wherein the analyzing is performed using at least one of acoustic modeling techniques or language modeling techniques.

19. A method for generating closed captions, the method comprising:

obtaining one or more text transcripts corresponding to one or more speech segments from an audio signal;

identifying an appropriate context associated with the one or more text transcripts based on a topic specific word probability count in the text transcripts;

processing the one or more text transcripts for word errors; and

broadcasting the one or more text transcripts as closed captions in conjunction with the audio signal.

20. A computer-readable medium storing computer instructions for instructing a computer system for generating closed captions, the computer instructions comprising:

obtaining one or more text transcripts corresponding to one or more speech segments from an audio signal;

identifying an appropriate context associated with the one or more text transcripts; and

processing the one or more text transcripts for word errors; and

broadcasting the one or more text transcripts corresponding to the speech segments as closed captions.