# How Speech Recognizers Use Expected Answers to Speed Up > This patent describes how a speech recognition system can get faster and more accurate by first checking if what you said matches what it expects you to say, instead of listening for everything. - **Patent:** US 8612235 - **Original title:** Method and system for considering information about an expected response when performing speech recognition - **Owner:** Vocollect - **Granted:** 2013 - **Status:** Active - **Times cited:** 6 - **Field:** telecommunications, software, consumer_electronics, ai_ml ## What it does This patent describes a method for a speech recognition system to process user input more efficiently. During a conversation, or "speech dialog," the system identifies a set of highly probable user responses, called the "expected response," which is a smaller part of all possible answers (the "grammar of possible responses"). Instead of comparing the sounds it hears (the "acoustic features") to every single possible word, the system first compares these sounds *only* to the sound pattern (the "model") of the expected response (Claim 1). If this initial comparison yields a high enough "confidence factor" compared to an "acceptance threshold," the system quickly accepts the expected response. If not, it can then proceed to compare the input to models for other possible responses (Claim 3). For example, if a voice assistant asks "Yes or No?" it would first check if the user's speech matches the models for "yes" or "no" before searching for other words. ## What it does NOT cover - Speech recognition systems that always compare input speech to all possible responses in a grammar simultaneously without prioritizing expected responses. - Systems that do not have a pre-determined "expected response" known before the user speaks. - Speech recognition that doesn't use a "confidence factor" and "acceptance threshold" for the expected response. - Systems that do not perform an initial, direct comparison *only* to the expected response model before considering other options. ## The clever bit The core innovation is the initial, focused comparison of incoming speech *only* against the sound model of the *expected* response. This avoids the computational cost of a full search across all possible responses, making the system faster and more efficient when the user's input aligns with expectations. ## Real-world examples 1. Voice-controlled inventory management systems (e.g., in warehouses) 2. Interactive Voice Response (IVR) systems for customer service 3. Smart home voice commands where the system expects a specific action (e.g., "on" or "off") 4. In-car voice commands for navigation or media control ## Why it matters This approach significantly improves the efficiency and accuracy of speech recognition, particularly in structured conversational flows like those found in voice assistants or industrial voice-picking systems. By focusing the initial search on the most likely answers, it reduces the computational load and the chance of misinterpretations. This method is valuable in environments where quick and reliable voice interactions are critical, making voice-controlled systems more practical. ## Frequently asked questions ### What does How Speech Recognizers Use Expected Answers to Speed Up cover? This patent describes how a speech recognition system can get faster and more accurate by first checking if what you said matches what it expects you to say, instead of listening for everything. ### Who owns patent US 8612235? Vocollect owns this patent, granted in 2013. ### When does this patent expire? This patent is expected to expire on June 8, 2032, when the invention enters the public domain. ### What is patent US 8612235 cited by? This patent has been cited by 6 later patents that build on its ideas. ### What problem does this patent solve? This approach significantly improves the efficiency and accuracy of speech recognition, particularly in structured conversational flows like those found in voice assistants or industrial voice-picking systems. By focusing the initial search on the most likely answers, it reduces the computational load and the chance of misinterpretations. This method is valuable in environments where quick and reliable voice interactions are critical, making voice-controlled systems more practical. ### What does this patent NOT cover? Speech recognition systems that always compare input speech to all possible responses in a grammar simultaneously without prioritizing expected responses. **Full plain-English explainer:** https://patentbrief.org/patent/us/8612235/method-and-system-for-considering-information-about-an-expected-response-when-pe **Original patent:** https://patents.google.com/patent/US8612235 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How Smart Speakers Know You're Talking to Them After a Command](https://patentbrief.org/patent/us/11361763/detecting-system-directed-speech) — This patent describes how a smart speaker system can tell if follow-up speech is meant for it, even without a "wake word," by analyzing voice activity and partial speech recognition results using an AI model. - [How Voice Assistants Change Their Speech Based on How You Talk](https://patentbrief.org/patent/us/10276149/dynamic-text-to-speech-output) — This patent describes a system where a voice-controlled device adjusts its text-to-speech output characteristics, like speed or tone, based on the user's speaking habits or current situation, making responses feel more natural and personalized. - [How Voice Assistants Recognize Who is Talking](https://patentbrief.org/patent/us/11514901/anchored-speech-detection-and-speech-recognition) — This patent describes a system that uses a recorded voice sample to identify if new speech comes from the same person, allowing voice assistants to only respond to specific users. - [How AI Predicts Who Will Speak Next in a Conversation](https://patentbrief.org/patent/us/11645473/palm-pathways-language-model) — IBM's patent describes a system that uses neural networks to analyze speech patterns and intentions to predict which person will talk next in a conversation. - [Making Computer Voices Sound More Expressive from Your Speech](https://patentbrief.org/patent/us/11062694/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.