Multilingual Command Recognition for Mixed-Language Speech Input
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Speech recognition systems struggle to accurately interpret audio commands from diverse populations that speak multiple languages, particularly in environments where languages are comingled, such as Spanglish.
Innovation Solution
A speech recognition system that utilizes multiple linguistic models to generate transcripts, processes phrases, applies heuristic rules and command patterns, and filters match phrases to select appropriate operational commands, enhancing accuracy in mixed-language environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single language-based recognition system is used, then the system complexity is reduced, but the ability to recognize and interpret audio commands from diverse populations speaking multiple languages deteriorates
Solution Approach 1:
The patent implements a speech recognition system that can process multiple languages (English, Spanish, and other languages) within a single unified system. The system uses multiple acoustic models and language models that can be selectively activated based on the detected language, allowing one system to serve diverse populations without requiring separate specialized systems for each language.
Solution Approach 2:
The system dynamically adapts its language processing capabilities by detecting the language of the audio input and selecting appropriate acoustic and language models accordingly. This dynamic language detection and model selection allows the system to adjust its behavior based on the spoken language, enabling it to handle multilingual environments effectively while maintaining manageable complexity through automated adaptation.
2Measurement precision
If a speech recognition system trained for different languages is used, then the recognition accuracy for single-language commands improves, but the effectiveness in linguistic environments where multiple languages are comingled deteriorates
Solution Approach 1:
The patent segments the speech recognition process into distinct components: acoustic model processing and language model processing. By separating these functions and allowing each to operate independently on different language data, the system can maintain high accuracy for individual languages while also handling mixed-language scenarios through the coordinated interaction of segmented processing stages.
Solution Approach 2:
The system introduces language detection as an intermediary step between acoustic processing and language model selection. This intermediary mechanism analyzes the audio input to determine the primary language and selectively activates appropriate acoustic and language models, enabling the system to maintain high recognition accuracy across single-language and mixed-language environments without requiring separate specialized systems.
3Measurement precision
If multiple linguistic models are used to process audio commands, then the recognition accuracy in multi-lingual contexts improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary language detection on the audio input before activating full acoustic and language model processing. This preliminary action identifies the primary language and allows the system to pre-select appropriate models, reducing the time required for subsequent processing by avoiding unnecessary model activation and enabling more efficient resource allocation.
Solution Approach 2:
The system applies partial processing by activating only the necessary acoustic and language models based on language detection results. Rather than processing all possible languages simultaneously, the system selectively processes the detected primary language and relevant secondary languages, reducing computational overhead and processing time while maintaining high recognition accuracy for the intended command.
Data Source
AI summary
Systems and methods are described for processing and interpreting audible commands spoken in one or more languages. Speech recognition systems disclosed herein may be used as a stand-alone speech recognition system or comprise a portion of another content consumption system. A requesting user may provide audio input (e.g., command data) to the speech recognition system via a computing device to request an entertainment system to perform one or more operational commands. The speech recognition system may analyze the audio input across a variety of linguistic models, and may parse the audio input to identify a plurality of phrases and corresponding action classifiers. In some embodiments, the speech recognition system may utilize the action classifiers and other information to determine the one or more identified phrases that appropriately match the desired intent and operational command associated with the user's spoken command.