science

Voice search

Voice search is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Voice search rather than just read about it. In short: Voice search, also called voice-enabled search, allows the user to use a voice to search the Internet, a website, or an app. In a broader definition, voice search includes open-domain keyword query on any information on the Internet, for example in Google Voice Search, Cortana, Siri and Amazon Echo.

Key takeaways

Voice search belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Voice search to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Voice search from memory before moving on to harder problems.

Reference excerpt

Voice search, also called voice-enabled search, allows the user to use a voice to search the Internet, a website, or an app. In a broader definition, voice search includes open-domain keyword query on any information on the Internet, for example in Google Voice Search, Cortana, Siri and Amazon Echo. Voice search is often interactive, involving several rounds of interaction that allows a system to ask for clarification. Voice search is a type of dialog system. Voice search is not a replacement for typed search. Rather the search terms, experience and use cases can differ heavily depending on the input type.

Supported language Language is the most essential factor for a system to understand, and provide the most accurate results of what the user searches. This covers across languages, dialects, and accents, as users want a voice assistant that both understands them and speaks to them understandably. While spoken and written languages differ, voice search should support natural spoken language instead of only transforming voice into text and doing a regular text search with the help speech recognition. For example, in typed search an eCommerce user can easily copy and paste an alphanumeric product code to search field, but when speaking the search terms can be very different, such as "show me the new Bluetooth headphones by Samsung".

How it works The difference between text and voice search is not only the input type. The mechanism must include an automatic speech recognition (ASR) for input, but it can also include natural language understanding for natural spoken search queries such as "What's the population for the United States" It can include text-to-speech (TTS) or a regular display for output modalities. Users might sometimes be required to activate the search by using a wake word. Then, the search system will detect the language spoken by the user. It will then detect the keywords and context of the sentence. Lastly, the device will return results depending on its output. A device with a screen might display the results, while a device without a screen will speak them back to the searcher.

Worked examples

Example 1 — a first encounter with Voice search

Start with the simplest possible case. Write down what Voice search claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Voice search before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Voice search ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Voice search

In research: Voice search appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Voice search in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Voice search is common in secondary-school and first-year university syllabi. It links to neighbouring topics Information retrieval genres, Speech recognition, so understanding it makes those chapters shorter.
In everyday life: Look for Voice search outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Voice search in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Voice search means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Voice search out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Voice search in simple terms?

Why does Voice search matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Voice search?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Voice search.