Speaker-Specific Speech Filter for Voice Assistant Noise Reduction
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Solution Overview
Problem
Voice assistant systems face challenges in noisy environments and multi-person interactions, leading to confusion and unsatisfactory user experiences due to difficulty in separating speech from background noise and distinguishing between multiple speakers.
Innovation Solution
A speaker-specific speech input filter is enabled based on detected speech signature data, which enhances the speech of a particular person by reducing background noise and removing speech from other individuals, thereby improving speech recognition accuracy and preventing interruptions during voice assistant sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech processing is performed in noisy environments without speaker-specific filtering, then the system can process any speech input, but speech recognition accuracy deteriorates due to background noise and multiple speakers
Solution Approach 1:
The patent segments the audio signal into speaker-specific components by obtaining speech signature data for different individuals and applying selective filtering. The speech input filter divides the mixed audio stream into distinct speaker channels, allowing the system to process each speaker's speech separately and improve recognition accuracy in multi-person environments.
Solution Approach 2:
The patent applies speaker-specific filtering selectively based on detected speech signatures. Instead of uniformly processing all audio input, the system identifies which speaker is currently speaking and applies enhanced filtering specifically for that speaker's voice characteristics, thereby improving speech recognition accuracy for the active speaker while maintaining system responsiveness.
2Measurement precision
If speaker-specific speech input filtering is always enabled, then speech recognition accuracy is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent dynamically adjusts the filtering behavior based on real-time detection of speech signatures and wake words. The speech input filter is selectively enabled or adjusted based on whether a wake word is detected and which speaker is currently active, rather than maintaining constant high-level filtering. This dynamic adaptation improves speech recognition accuracy when needed while reducing processing complexity during normal operation.
Solution Approach 2:
The system automatically detects speech signatures and determines when speaker-specific filtering should be applied without requiring manual configuration. The wake word detection and speech signature analysis are performed autonomously by the system, enabling it to self-adjust the filtering level based on the current acoustic environment and speaker presence, thereby balancing accuracy improvement with processing efficiency.
3Adaptability or versatility
If speech from multiple people is processed without differentiation, then the system responds to all inputs, but user experience deteriorates due to confusion and interruptions
Solution Approach 1:
The patent segments multi-person speech into distinct speaker channels by detecting and comparing speech signatures. When multiple people are present, the system identifies each speaker's unique voice characteristics and separates their speech streams, allowing the voice assistant to reliably determine which speaker's input should be processed and responded to, thereby preventing confusion and improving user experience.
Solution Approach 2:
The system uses feedback from wake word detection and speech signature analysis to dynamically adjust its response behavior. By continuously monitoring which speaker has activated the voice assistant and maintaining speaker-specific filtering, the system provides reliable and context-appropriate responses, preventing interruptions from unintended speakers and enhancing overall user experience quality.
Data Source
AI summary
A device includes one or more processors configured to, based on detection of a wake word in an utterance from a first person, obtain first speech signature data associated with the first person. The one or more processors are further configured to selectively enable a speaker-specific speech input filter that is based on the first speech signature data.