How Voice Assistants Distinguish Speakers After a Wakeword
This patent describes a method for voice assistants to better understand who is speaking after a 'wakeword' by comparing voice characteristics to improve speech recognition accuracy, especially in multi-speaker environments.
Original patent title: “Speech detection and speech recognition”
This patent describes a method for voice assistants to better understand who is speaking after a 'wakeword' by comparing voice characteristics to improve speech recognition accuracy, especially in multi-speaker environments. Granted to Amazon Technologies in 2021 with 23 claims and 35 forward citations, and it is expected to expire in 2039.
Coverage
What does this patent actually cover?
This patent outlines a computer-implemented method for automatic speech recognition that focuses on distinguishing between speakers after a 'wakeword' is detected. First, the system receives audio data and processes it to identify a 'wakeword' spoken by a 'first speaker' (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). It then takes subsequent portions of audio and compares their characteristics to those of the original wakeword. For example, if a second person speaks, the system determines a 'first similarity data' between the wakeword and that second person's speech (Claim 1). It then calculates a 'first weight' based on this similarity. If the original speaker continues, the system determines 'second similarity data' between the wakeword and the original speaker's continued speech, calculating a 'second weight' that is greater than the first (Claim 1). By comparing these weighted similarity measures, the system determines that the speech from the original speaker is 'more likely' to have come from the person who spoke the wakeword. Finally, it processes the speech from the original speaker to convert it into text and execute a command (Claim 1).
The gap
What does this patent NOT cover?
- Does not cover speech recognition systems that do not rely on a 'wakeword' to initiate the process.
- Does not cover general speaker identification or diarization that is not specifically tied to processing subsequent speech after a wakeword.
- Does not cover methods that do not use similarity data and calculated weights to distinguish between speakers after the wakeword.
- Does not cover systems where the 'second weight' is not determined to be greater than the 'first weight' when comparing the original speaker's subsequent speech to another speaker's speech.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → lies in using the initial 'wakeword' spoken by a specific person as a reference point. The system then generates 'similarity data' and 'weights' by comparing subsequent speech segments to the wakeword's unique audio characteristics. These weights help the system prioritize and accurately process commands from the intended speaker, even when other voices are present.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Amazon Echo devices
Google Nest Hub
Smart speakers with voice assistants
Voice-controlled smart home devices
Why it matters
The bigger picture
This technology is crucial for improving the accuracy and user experience of voice-controlled devices, especially in homes with multiple people. By precisely distinguishing who is speaking after a command, it helps voice assistants like Amazon Alexa or Google Assistant respond correctly to the intended user. This reduces errors and makes smart speakers more reliable and useful in everyday life.
Filed
March 28, 2019
Granted
February 16, 2021
Market context
Who's building on this
Companies in this space
Amazon Technologies Inc., the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is actively developing and implementing this technology within its Alexa ecosystem and smart devices. Other major technology companies like Google and Apple also invest heavily in similar speaker recognition and distinction technologies to enhance their respective voice assistant platforms, such as Google Assistant and Siri.
Market impact
This patent's technology contributes to the improved reliability and user experience of voice-controlled devices, which is vital for their widespread adoption. By enabling voice assistants to more accurately identify and respond to the intended speaker in multi-user environments, it helps reduce frustration and increases trust in these devices. This capability is a key factor in the continued growth and market penetration of smart speakers and voice-enabled smart home devices.
Claim 1 — Plain English
What this patent covers
This patent outlines a computer-implemented method for automatic speech recognition that focuses on distinguishing between speakers after a 'wakeword' is detected. First, the system receives audio data and processes it to identify a 'wakeword' spoken by a 'first speaker' (Claim 1). It then takes subsequent portions of audio and compares their characteristics to those of the original wakeword. For example, if a second person speaks, the system determines a 'first similarity data' between the wakeword and that second person's speech (Claim 1). It then calculates a 'first weight' based on this similarity. If the original speaker continues, the system determines 'second similarity data' between the wakeword and the original speaker's continued speech, calculating a 'second weight' that is greater than the first (Claim 1). By comparing these weighted similarity measures, the system determines that the speech from the original speaker is 'more likely' to have come from the person who spoke the wakeword. Finally, it processes the speech from the original speaker to convert it into text and execute a command (Claim 1).
The clever bit
The novelty lies in using the initial 'wakeword' spoken by a specific person as a reference point. The system then generates 'similarity data' and 'weights' by comparing subsequent speech segments to the wakeword's unique audio characteristics. These weights help the system prioritize and accurately process commands from the intended speaker, even when other voices are present.
What it does not cover
- Does not cover speech recognition systems that do not rely on a 'wakeword' to initiate the process.
- Does not cover general speaker identification or diarization that is not specifically tied to processing subsequent speech after a wakeword.
- Does not cover methods that do not use similarity data and calculated weights to distinguish between speakers after the wakeword.
- Does not cover systems where the 'second weight' is not determined to be greater than the 'first weight' when comparing the original speaker's subsequent speech to another speaker's speech.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
Patent enters public domain
PatentBrief Score
Impact Score
Strong
Citation count
31/40
Moderately cited
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
10/20
Granted 5–10 years ago
Assignee scale
20/20
Major company or institution
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$263K – $842K
Midpoint $527K · 12.4 yr remaining · industry ×1.5
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Liu, Y., Chen, I., Fan, X., Wang, Y., Hoffmeister, B., & Chen, T. (2021). How Voice Assistants Distinguish Speakers After a Wakeword (U.S. Patent No. 10,923,111). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/10923111/speech-detection-and-speech-recognition
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Voice Assistants Distinguish Speakers After a Wakeword cover?
This patent describes a method for voice assistants to better understand who is speaking after a 'wakeword' by comparing voice characteristics to improve speech recognition accuracy, especially in multi-speaker environments.
Who owns patent US 10923111?
Amazon Technologies owns this patent, granted in 2021.
When does this patent expire?
This patent is expected to expire on March 28, 2039, when the invention enters the public domain.
What is patent US 10923111 cited by?
This patent has been cited by 35 later patents that build on its ideas.
What problem does this patent solve?
This technology is crucial for improving the accuracy and user experience of voice-controlled devices, especially in homes with multiple people. By precisely distinguishing who is speaking after a command, it helps voice assistants like Amazon Alexa or Google Assistant respond correctly to the intended user. This reduces errors and makes smart speakers more reliable and useful in everyday life.
What does this patent NOT cover?
Does not cover speech recognition systems that do not rely on a 'wakeword' to initiate the process.
Same assignee
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