TiVo Corporation (20240347053). GENERATING TOPIC-SPECIFIC LANGUAGE MODELS simplified abstract
Contents
- 1 GENERATING TOPIC-SPECIFIC LANGUAGE MODELS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 GENERATING TOPIC-SPECIFIC LANGUAGE MODELS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Speech Recognition Technology
- 1.13 Original Abstract Submitted
GENERATING TOPIC-SPECIFIC LANGUAGE MODELS
Organization Name
Inventor(s)
David F. Houghton of Brattleboro VT (US)
Seth Michael Murray of Redwood City CA (US)
Sibley Verbeck Simon of Santa Cruz CA (US)
GENERATING TOPIC-SPECIFIC LANGUAGE MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240347053 titled 'GENERATING TOPIC-SPECIFIC LANGUAGE MODELS
Simplified Explanation
The patent application discusses improving speech recognition by creating a topic-specific language model based on the content of the audio signal.
Key Features and Innovation
- Initial pass on audio signal using a generic language model
- Determining topics based on identified words
- Retrieving a corpus of text related to those topics
- Creating a topic-specific language model using the retrieved text
- Adapting the generic language model based on the retrieved corpus
Potential Applications
This technology can be applied in various fields such as:
- Voice-controlled devices
- Transcription services
- Language translation tools
Problems Solved
- Enhances accuracy of speech recognition
- Improves understanding of context in audio signals
- Enables better communication with voice-activated systems
Benefits
- Increased efficiency in speech recognition
- Enhanced user experience with voice-controlled devices
- Improved accuracy in transcribing audio content
Commercial Applications
- This technology can be utilized in developing advanced speech recognition systems for commercial use, such as in customer service centers, transcription services, and language learning platforms.
Prior Art
Prior art related to this technology may include research on topic modeling in natural language processing and speech recognition systems.
Frequently Updated Research
Stay updated on advancements in natural language processing, speech recognition, and topic modeling to enhance the capabilities of this technology.
Questions about Speech Recognition Technology
How does a topic-specific language model improve speech recognition accuracy?
A topic-specific language model helps the system better understand the context of the audio signal, leading to more accurate transcription and interpretation.
What are the potential challenges in implementing a topic-specific language model in speech recognition devices?
Implementing a topic-specific language model may require significant computational resources and a large corpus of text data for training, which can be a challenge for some systems.
Original Abstract Submitted
speech recognition may be improved by generating and using a topic specific language model. a topic specific language model may be created by performing an initial pass on an audio signal using a generic or basis language model. a speech recognition device may then determine topics relating to the audio signal based on the words identified in the initial pass and retrieve a corpus of text relating to those topics. using the retrieved corpus of text, the speech recognition device may create a topic specific language model. in one example, the speech recognition device may adapt or otherwise modify the generic language model based on the retrieved corpus of text.
