Speech Playback Attenuation Using Ambient Sound Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech recognition systems discard audio interruption data, missing opportunities to enhance user experience by not responding intelligently to ambient background noises or other audio events without user prompting, despite a growing need for smarter devices that anticipate user needs.
Innovation Solution
A speech-enabled device that monitors for audio interruptions, modifies activities such as pausing applications or adjusting volume based on recognized sounds like a doorbell or phone ringing, and then waits for a user command to restore the original state, using a combination of speech recognition and acoustic fingerprinting techniques to differentiate between speech and ambient noises.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition systems discard audio interruption data to focus on speech identification, then speech recognition accuracy is improved, but the ability to respond to ambient background noises is lost
Solution Approach 1:
The audio processing system is segmented into two distinct pathways: one dedicated to speech recognition that filters and processes only speech-related audio data, and another dedicated to audio interruption detection that processes non-speech ambient sounds. This segmentation allows each pathway to optimize its performance for its specific function without interfering with the other, resolving the contradiction between speech recognition accuracy and ambient noise responsiveness.
Solution Approach 2:
The patent merges speech recognition and audio interruption detection into a single integrated system that processes audio data simultaneously through multiple classification models. The system combines the strengths of both functions by maintaining separate processing streams that converge to provide comprehensive audio understanding, enabling the device to both accurately recognize speech and intelligently respond to ambient noises.
2Ease of operation
If the device responds to every audio interruption with user prompting, then user control is maintained, but user experience deteriorates due to excessive interruptions
Solution Approach 1:
The system implements self-service by automatically detecting audio interruptions and autonomously determining appropriate responses without requiring user prompting. The acoustic fingerprinting engine independently identifies ambient noises such as doorbells or phone rings and triggers context-appropriate actions, allowing the device to serve itself and reducing the burden on the user while maintaining effective control.
Solution Approach 2:
The system incorporates feedback mechanisms where the detected audio interruption type informs the response strategy. The acoustic fingerprinting engine provides feedback about the nature of ambient sounds to the control system, which then adjusts its behavior accordingly - responding automatically to certain interruptions while maintaining user control for others, optimizing both ease of operation and productivity.
3Device complexity
If the device uses only speech recognition to identify user intent, then system simplicity is maintained, but responsiveness to non-speech audio events is lost
Solution Approach 1:
The audio processing system is designed with multi-functionality to handle both speech recognition and audio interruption detection using a unified architecture. The same audio input stream is processed by multiple classification models simultaneously - one optimized for speech identification and another for ambient noise detection. This universal approach allows the system to perform diverse functions without requiring separate dedicated systems, maintaining relative simplicity while expanding adaptability.
Data Source
AI summary
A speech recognition system that also automatically recognizes and acts in response to significant audio interruptions. Received audio is compared with stored acoustic signatures of noises which may trigger a change in device operation, such as pausing, loudening or attenuating of content playback after hearing a certain audio interruption, such as a doorbell, etc. If the received audio matches a stored acoustic model, the system alters an operational state of one or more devices, which may or may not include itself.