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Onset (audio)

Onset (audio) 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 Onset (audio) rather than just read about it. In short: Onset refers to the beginning of a musical note or other sound. It is related to (but different from) the concept of a transient: all musical notes have an onset, but do not necessarily include an initial transient.

Key takeaways

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

Reference excerpt

Onset refers to the beginning of a musical note or other sound. It is related to (but different from) the concept of a transient: all musical notes have an onset, but do not necessarily include an initial transient.

Onset detection In signal processing, onset detection is an active research area. For example, the MIREX annual competition features an Audio Onset Detection contest. Approaches to onset detection can operate in the time domain, frequency domain, phase domain, or complex domain, and include looking for:

Increases in spectral energy Changes in spectral energy distribution (spectral flux) or phase Changes in detected pitch - e.g. using a polyphonic pitch detection algorithm Spectral patterns recognisable by machine learning techniques such as neural networks. Simpler techniques such as detecting increases in time-domain amplitude can typically lead to an unsatisfactorily high amount of false positives or false negatives. The aim is often to judge onsets similarly to how a human would: so psychoacoustically-motivated strategies may be employed. Sometimes the onset detector can be restricted to a particular domain (depending on intended application), for example being targeted at detecting percussive onsets. With a narrower focus, it can be more straightforward to obtain reliable detection.

See also ADSR envelope Prefix (acoustics)

References Bello, J.P., Daudet, L., Abdallah, S., Duxbury, C., Davies, M., Sandler, M.B. (2005) "A Tutorial on Onset Detection in Music Signals", IEEE Transactions on Speech and Audio Processing 13(5), pp 1035–1047 Bello, J.P, Duxbury, C., Davies, M., Sandler, M. (2004). "On the use of phase and energy for musical onset detection in the complex domain". IEEE Signal Processing Letters Collins, N. (2005) "A Comparison of Sound Onset Detection Algorithms with Emphasis on Psychoacoustically Motivated Detection Functions". Proceedings of AES118 Convention

Worked examples

Example 1 — a first encounter with Onset (audio)

Start with the simplest possible case. Write down what Onset (audio) 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 Onset (audio) 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 Onset (audio) 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 Onset (audio)

In research
Onset (audio) 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 Onset (audio) 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
Onset (audio) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Psychoacoustics, Signal processing stubs, Synthesizers, so understanding it makes those chapters shorter.
In everyday life
Look for Onset (audio) 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 Onset (audio) in 20 minutes

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

Frequently asked questions

What is Onset (audio) in simple terms?

Onset refers to the beginning of a musical note or other sound. It is related to (but different from) the concept of a transient: all musical notes have an onset, but do not necessarily include an initial transient.

Why does Onset (audio) 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 Onset (audio)?

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 Onset (audio).

Tags

  • Psychoacoustics
  • Signal processing stubs
  • Synthesizers

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