View source for 18389033. AUTOMATICALLY DETERMINING LANGUAGE FOR SPEECH RECOGNITION OF SPOKEN UTTERANCE RECEIVED VIA AN AUTOMATED ASSISTANT INTERFACE simplified abstract (Google LLC)

=AUTOMATICALLY DETERMINING LANGUAGE FOR SPEECH RECOGNITION OF SPOKEN UTTERANCE RECEIVED VIA AN AUTOMATED ASSISTANT INTERFACE=


==Organization Name==

[[:Category:Google LLC|Google LLC]]


[[Category:Google LLC]]

==Inventor(s)==

[[:Category:Pu-sen Chao of Los Altos CA (US)|Pu-sen Chao of Los Altos CA (US)]][[Category:Pu-sen Chao of Los Altos CA (US)]]

[[:Category:Diego Melendo Casado of Mountain View CA (US)|Diego Melendo Casado of Mountain View CA (US)]][[Category:Diego Melendo Casado of Mountain View CA (US)]]

[[:Category:Ignacio Lopez Moreno of New York NY (US)|Ignacio Lopez Moreno of New York NY (US)]][[Category:Ignacio Lopez Moreno of New York NY (US)]]

==AUTOMATICALLY DETERMINING LANGUAGE FOR SPEECH RECOGNITION OF SPOKEN UTTERANCE RECEIVED VIA AN AUTOMATED ASSISTANT INTERFACE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18389033 titled 'AUTOMATICALLY DETERMINING LANGUAGE FOR SPEECH RECOGNITION OF SPOKEN UTTERANCE RECEIVED VIA AN AUTOMATED ASSISTANT INTERFACE

Abstract: Implementations relate to determining a language for speech recognition of a spoken utterance, received via an automated assistant interface, for interacting with an automated assistant. Implementations can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. Selection of a speech recognition model for a particular language can based on one or more interaction characteristics exhibited during a dialog session between a user and an automated assistant. Such interaction characteristics can include anticipated user input types, anticipated user input durations, a duration for monitoring for a user response, and/or an actual duration of a provided user response.

**Key Features and Innovation:**
- Determining language for speech recognition without user input
- Multilingual interaction with automated assistant
- Selection of speech recognition model based on interaction characteristics

**Potential Applications:**
This technology can be applied in:
- Automated customer service systems
- Language learning applications
- Multilingual virtual assistants

**Problems Solved:**
- Eliminates the need for users to specify language for each interaction
- Enhances user experience with automated assistants
- Improves accuracy of speech recognition in multilingual environments

**Benefits:**
- Seamless multilingual interaction
- Enhanced user convenience
- Improved efficiency in automated assistant interactions

**Commercial Applications:**
This technology can be utilized in various industries such as customer service, education, and technology to enhance multilingual communication with automated systems.

**Prior Art:**
Prior research in speech recognition and language processing technologies may provide insights into similar approaches to multilingual interaction with automated assistants.

**Frequently Updated Research:**
Stay updated on advancements in speech recognition technologies and multilingual interaction methods to enhance the capabilities of automated assistants.

**Questions about Multilingual Speech Recognition:**
1. How does this technology improve user experience with automated assistants?
2. What are the potential challenges in implementing multilingual speech recognition in automated systems?


==Original Abstract Submitted==

Implementations relate to determining a language for speech recognition of a spoken utterance, received via an automated assistant interface, for interacting with an automated assistant. Implementations can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. Selection of a speech recognition model for a particular language can based on one or more interaction characteristics exhibited during a dialog session between a user and an automated assistant. Such interaction characteristics can include anticipated user input types, anticipated user input durations, a duration for monitoring for a user response, and/or an actual duration of a provided user response.



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