Speech Recognition Disambiguation via Background Audio Context
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Solution Overview
Problem
Speech recognition systems often misinterpret ambiguous voice inputs due to lack of contextual information, leading to errors in tasks such as text generation and search queries, especially when background audio is not considered.
Innovation Solution
A method that separates user speech data from background audio in an audio stream, identifies concepts related to the background audio, and uses these concepts to influence the speech recognition process, improving accuracy by providing contextual clues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition systems process audio streams without considering background audio, then the processing speed is maintained, but the accuracy of speech recognition deteriorates due to ambiguous voice inputs
Solution Approach 1:
The audio stream is segmented into multiple components: foreground speech signals and background audio signals. This segmentation allows the system to process each component separately, identifying concepts from background audio (such as music genre, artist, or lyrical themes) and using these concepts to disambiguate the foreground speech recognition, thereby improving accuracy without proportionally increasing overall complexity
Solution Approach 2:
Background audio concepts serve as an intermediary element that mediates between the raw audio stream and the speech recognition process. By extracting semantic information from background audio (e.g., if background music is from a specific movie or show, extracting related entities), the system creates contextual clues that help resolve ambiguities in speech recognition without requiring direct complex interaction between all audio components
2Measurement precision
If speech recognition systems separate and analyze background audio to improve accuracy, then the measurement precision improves, but the processing time increases
Solution Approach 1:
The system performs preliminary analysis of background audio by extracting and storing conceptual information (such as music metadata, program information, or environmental sound characteristics) before the speech recognition process begins. This pre-extracted contextual information is then readily available to assist speech disambiguation, reducing the real-time processing burden during actual speech recognition tasks
Data Source
AI summary
Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.