GOOGLE LLC (20240233712). Speech Recognition Biasing simplified abstract
Contents
Speech Recognition Biasing
Organization Name
Inventor(s)
Olawale Abiri of Westfield NJ (US)
Dharmeshkumar Jayantilal Mokani of Milpitas CA (US)
Speech Recognition Biasing - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240233712 titled 'Speech Recognition Biasing
Simplified Explanation: The patent application describes a method for biasing speech recognition based on context data to improve transcription accuracy.
Key Features and Innovation:
- Receiving a speech recognition request with audio data and configuration parameters.
- Processing audio data using a speech recognition model to generate scores for speech elements.
- Determining context scores for speech elements based on configuration parameters and context data.
- Biasing speech recognition scores using context scores to improve transcription accuracy.
Potential Applications: This technology can be applied in various fields such as virtual assistants, customer service chatbots, transcription services, and language translation tools.
Problems Solved: This technology addresses the challenge of improving speech recognition accuracy by considering context data to provide more accurate transcriptions.
Benefits:
- Enhanced transcription accuracy.
- Improved user experience with speech recognition applications.
- Increased efficiency in processing speech data.
Commercial Applications: The technology can be utilized in developing advanced speech recognition systems for commercial use, such as in call centers, language learning applications, and voice-controlled devices.
Prior Art: Readers can explore prior research in the fields of natural language processing, machine learning, and speech recognition to understand the evolution of biasing techniques in speech recognition.
Frequently Updated Research: Stay updated on advancements in speech recognition models, context-aware algorithms, and applications of biasing techniques in improving transcription accuracy.
Questions about Speech Recognition Biasing: 1. How does biasing speech recognition scores using context data improve transcription accuracy? 2. What are the potential limitations of biasing techniques in speech recognition systems?
Original Abstract Submitted
a method for speech recognition biasing includes receiving, from an application executing on a user device, at a speech service interface, a speech recognition request requesting a transcription of an utterance. the speech recognition request includes audio data encoding the utterance and configuration parameters for biasing a speech recognition model based on context data. the method includes processing, using the speech recognition model, the audio data to generate speech recognition scores for speech elements and determining context scores for the speech elements based on the configuration parameters and the context data. the method includes biasing the speech recognition scores using the context scores. the method also includes determining the transcription for the utterance based on the biased speech recognition scores.
