International business machines corporation (20240161733). GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS simplified abstract
Contents
- 1 GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS
Organization Name
international business machines corporation
Inventor(s)
GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161733 titled 'GENERATION OF TRAINING EXAMPLES FOR TRAINING AUTOMATIC SPEECH RECOGNIZERS
Simplified Explanation
The present invention involves a method, computer program product, and computer system for generating training examples for training an automatic speech recognizer. The method includes receiving a training dataset of original audio signals and generating training examples based on a constructed imperceptible space for the original audio signals and adversarial audio examples in the constructed imperceptible space. An imperceptible and adversarial audio example is then generated for an adversarial trainer for the automatic speech recognizer.
- Training examples generated for training an automatic speech recognizer
- Based on imperceptible space for original audio signals and adversarial audio examples
- Imperceptible and adversarial audio examples created for training
- Utilizes a training dataset of original audio signals
Potential Applications
The technology can be applied in:
- Improving the accuracy and performance of automatic speech recognition systems
- Enhancing the robustness of speech recognition in noisy environments
Problems Solved
This technology addresses:
- Challenges in training automatic speech recognizers with diverse audio signals
- Overcoming limitations in traditional speech recognition training methods
Benefits
The benefits of this technology include:
- Increased accuracy and reliability of automatic speech recognition systems
- Improved adaptability to different audio environments
- Enhanced overall performance of speech recognition systems
Potential Commercial Applications
With its capabilities, this technology can be utilized in various commercial applications such as:
- Voice-controlled devices and virtual assistants
- Call center automation systems
- Speech-to-text transcription services
Possible Prior Art
One possible prior art in this field is the use of adversarial training techniques in machine learning to improve model robustness and performance.
Unanswered Questions
How does this technology compare to traditional speech recognition training methods?
This technology improves upon traditional methods by incorporating imperceptible spaces and adversarial examples for more effective training. It would be interesting to see a comparative study showcasing the performance differences between the two approaches.
What impact does the imperceptible space have on the generated training examples?
The concept of imperceptible space is crucial in this technology, but the specific effects and benefits it provides to the training examples could be further explored and explained in detail.
Original Abstract Submitted
a method, computer program product, and computer system for generation of training examples for training an automatic speech recognizer. embodiments of the present invention can receive a training dataset of original audio signals and generate training examples for training an automatic speech recognizer based, at least in part, on a constructed imperceptible space for an original audio signal of the original audio signals and adversarial audio examples in the constructed imperceptible space. embodiments of the present invention can then generate an imperceptible and adversarial audio example to an adversarial trainer for the automatic speech recognizer.
