Making Computer Voices Sound More Expressive from Your Speech
This patent describes how a computer listens to your spoken words, figures out which parts you emphasized, and then makes its own computer-generated voice emphasize those same parts when it speaks back.
Original patent title: “Text-to-speech processing with emphasized output audio”
This patent describes how a computer listens to your spoken words, figures out which parts you emphasized, and then makes its own computer-generated voice emphasize those same parts when it speaks back. Granted to Amazon Technologies in 2021 with 20 claims and 3 forward citations, and it is expected to expire in 2039.
Coverage
What does this patent actually cover?
This patent describes a method for generating computer speech that mimics the emphasis from a user's original spoken input. First, the system receives input audio data representing speech and uses Automatic Speech Recognition (ASR) to convert it into text, referred to as "input data" (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). Then, it analyzes the input audio to determine "paralinguistic feature data" (Claim 1), which includes characteristics like pitch, volume, or duration of specific words. This paralinguistic data is used to identify which parts of the text should be emphasized. For example, if a user says "I *really* want coffee," the system detects the emphasis on "really." The system then prepares "output data" (Claim 1), potentially by adding a Speech Synthesis Markup Language (SSML) tag (Claim 4) to the emphasized portion. Finally, Text-to-Speech (TTS) processing is performed on this output data, generating speech where the identified portion, like "really," is spoken with corresponding emphasis (Claim 2), making the computer's response sound more natural.
The gap
What does this patent NOT cover?
- Does not cover text-to-speech emphasis based solely on linguistic rules or grammar without analyzing the user's original spoken input for paralinguistic features.
- Does not cover systems that only transcribe speech to text without generating new, emphasized speech output.
- Does not cover emphasizing computer-generated speech based purely on pre-written text where no input audio was analyzed for emphasis cues.
- Does not cover systems where emphasis is determined solely by user preferences or profile data without considering the paralinguistic features of the current input audio.
- Does not cover emphasis derived from non-audio inputs, such as visual cues or typed instructions, without corresponding analysis of spoken audio.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is directly linking the *way* a person speaks (their emphasis, pitch, or duration, called "paralinguistic feature data") from their input audio to how a computer then generates its own speech. Instead of just guessing which words to emphasize, the system uses the actual human vocal cues to make its response sound more natural.
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 Alexa
Google Assistant
Apple Siri
Microsoft Cortana
Voice-enabled smart home devices
Why it matters
The bigger picture
This patent is important for making interactions with voice assistants and other spoken interfaces feel more natural and intuitive. By understanding *how* a user speaks, not just *what* they say, systems can respond with more appropriate vocal emphasis. This improves the user experience, making computer-generated speech less robotic and more engaging, which is crucial for widespread adoption of voice-controlled devices.
Filed
June 7, 2019
Granted
July 13, 2021
Market context
Who's building on this
Companies in this space
Amazon, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, continues to build on this technology for its Alexa voice assistant. Other major players in the voice AI space, such as Google with Google Assistant and Apple with Siri, also develop and refine systems that aim to make computer-generated speech more natural and contextually aware. Many startups focused on conversational AI and synthetic media also explore advanced Text-to-Speech capabilities.
Market impact
This type of technology has significantly improved the user experience for voice assistants and other conversational AI systems. By allowing computer voices to reflect the nuance and emphasis of human speech, it has made interactions feel less robotic and more intuitive. This contributes to the broader adoption of voice-controlled devices and services, making them more accessible and pleasant to use for a wider range of applications.
Claim 1 — Plain English
What this patent covers
This patent describes a method for generating computer speech that mimics the emphasis from a user's original spoken input. First, the system receives input audio data representing speech and uses Automatic Speech Recognition (ASR) to convert it into text, referred to as "input data" (Claim 1). Then, it analyzes the input audio to determine "paralinguistic feature data" (Claim 1), which includes characteristics like pitch, volume, or duration of specific words. This paralinguistic data is used to identify which parts of the text should be emphasized. For example, if a user says "I *really* want coffee," the system detects the emphasis on "really." The system then prepares "output data" (Claim 1), potentially by adding a Speech Synthesis Markup Language (SSML) tag (Claim 4) to the emphasized portion. Finally, Text-to-Speech (TTS) processing is performed on this output data, generating speech where the identified portion, like "really," is spoken with corresponding emphasis (Claim 2), making the computer's response sound more natural.
The clever bit
The clever part is directly linking the *way* a person speaks (their emphasis, pitch, or duration, called "paralinguistic feature data") from their input audio to how a computer then generates its own speech. Instead of just guessing which words to emphasize, the system uses the actual human vocal cues to make its response sound more natural.
What it does not cover
- Does not cover text-to-speech emphasis based solely on linguistic rules or grammar without analyzing the user's original spoken input for paralinguistic features.
- Does not cover systems that only transcribe speech to text without generating new, emphasized speech output.
- Does not cover emphasizing computer-generated speech based purely on pre-written text where no input audio was analyzed for emphasis cues.
- Does not cover systems where emphasis is determined solely by user preferences or profile data without considering the paralinguistic features of the current input audio.
- Does not cover emphasis derived from non-audio inputs, such as visual cues or typed instructions, without corresponding analysis of spoken audio.
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
Moderate
Citation count
12/40
Early citations
Claim breadth
13/20
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
$70K – $225K
Midpoint $140K · 12.8 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
20 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Nicolis, M., & Nadolski, A. F. (2021). Making Computer Voices Sound More Expressive from Your Speech (U.S. Patent No. 11,062,694). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/11062694/text-to-speech-processing-with-emphasized-output-audio
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 Making Computer Voices Sound More Expressive from Your Speech cover?
This patent describes how a computer listens to your spoken words, figures out which parts you emphasized, and then makes its own computer-generated voice emphasize those same parts when it speaks back.
Who owns patent US 11062694?
Amazon Technologies owns this patent, granted in 2021.
When does this patent expire?
This patent is expected to expire on June 7, 2039, when the invention enters the public domain.
What is patent US 11062694 cited by?
This patent has been cited by 3 later patents that build on its ideas.
What problem does this patent solve?
This patent is important for making interactions with voice assistants and other spoken interfaces feel more natural and intuitive. By understanding *how* a user speaks, not just *what* they say, systems can respond with more appropriate vocal emphasis. This improves the user experience, making computer-generated speech less robotic and more engaging, which is crucial for widespread adoption of voice-controlled devices.
What does this patent NOT cover?
Does not cover text-to-speech emphasis based solely on linguistic rules or grammar without analyzing the user's original spoken input for paralinguistic features.
Same assignee
More from Amazon Technologies
Patent monitoring