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A speech recognition system takes natural speech audio as input and produces a coded representation of what was said—such as words, a command, or a sentence. It may be implemented in hardware, software, or both. The term often refers to automatic speech recognition (ASR), also called speech-to-text when the output is text.
What is a speech recognition system?
ITU-T P.10/G.100 Amendment 2, published in May 2024, defines an automatic speech recognition (ASR) system as “an implementation in hardware or software that accepts a natural speech signal as an input and provides, at the output, a coded version of what has been said.” That output could represent a word, command, expression, or sentence. ITU-T P.10/G.100 Amendment 2
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The U.S. Section 508 glossary similarly describes ASR as computer hardware- and software-based procedures for identifying and processing words spoken into a system. Section 508 glossary
What does it do—and what does it not do?
Recognition identifies the words or commands represented by the speech signal. It does not, by itself, necessarily determine what a speaker intends. A separate natural-language-understanding component may interpret context and intent after recognition. Amazon’s Alexa Skills Kit describes ASR as converting spoken words into text and treats language understanding as a further step. Alexa Skills Kit: understanding how users interact with skills
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How does a speech recognition system work?
At a basic level, an audio source supplies speech, a recognition engine processes the signal, and the system returns a textual or otherwise coded result. An implementation may involve a microphone, hardware, software runtime or API, recognition models, and vocabulary or grammar constraints. The components and arrangement vary by system.
For example, Microsoft documents Windows APIs that can transcribe recorded audio in a batch or recognize speech as it arrives from a microphone or another real-time source. Its Windows app guidance also describes predefined dictation and web-search grammars, as well as custom lists and SRGS constraints. These are examples of Windows implementations, not universal requirements. Microsoft: speech recognition APIs
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What kinds of speech recognition are there?
Dictation and transcription
These systems turn spoken language into text. They may process a previously recorded file or transcribe incoming audio as it is spoken, depending on the implementation.
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A command recognizer identifies expected phrases or commands, often using a defined vocabulary or grammar. Constraints can help a system focus on the phrases relevant to a particular task.
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Search, captions, and hands-free input
Speech recognition is also used for voice search, captions for meetings or media, accessibility-related speech input, and hands-free interactions. The supported task and vocabulary depend on the system and its configuration.
Can speech recognition run online or on a device?
Both deployment patterns exist. A system may process speech on the device or use a remote service; some implementations also support both recorded-audio batches and live streams. Network needs and privacy implications therefore depend on the specific product and mode.
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Microsoft’s Windows app documentation says its predefined dictation and web-search grammars use a remote service, require a network connection, and recognize up to 10 seconds of speech input. That limit and connection requirement apply to those documented grammars, not to speech recognition generally. Microsoft: SpeechRecognizer class
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What should you check when choosing or evaluating a system?
The definition alone does not establish how well a particular system performs. For a meaningful evaluation, compare the intended use and conditions rather than relying on an unsupported accuracy percentage.
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- Input: Which audio sources and microphones are supported, and what sound conditions are expected?
- Language and vocabulary: Which languages and phrases can it recognize? Is it intended for open dictation or a limited command set?
- Processing mode: Does it handle recorded audio, live streaming, or both?
- Deployment: Is processing on-device, remote, or configurable? Does the chosen mode require a network connection?
- Testing: Are the test conditions representative of the commands, speakers, and environment where it will be used?
For voice-command systems specifically, ISO/IEC 30122-2:2017 sets out criteria and test methods for voice commands and their recognition engine. ISO reports that the standard was confirmed in 2024 and remains current. It concerns command criteria and testing, rather than defining every kind of speech recognition system. ISO/IEC 30122-2:2017
Does a speech recognition system require a separate microphone?
Not necessarily. A microphone is one possible way to capture speech, and a device may already have a built-in audio input. Microsoft’s documentation describes recognition from a connected, enabled microphone in a particular Windows app flow, but that does not mean every system or user needs to buy an external microphone. Check the input requirements for the specific device and application.
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