laughter
Enable an AI agent to recognise and describe an episode of laughter, assess its ongoing state and interactional significance, and choose an appropriate response without assuming what the person feels.
Bundle → Layer → Finding → Questions Filled
4 bundles · 8 layers · 8 findings · 16 questions
Laughter recognition Establishes whether the available evidence supports recognising an expression as laughter.
Expressive evidence
Records the audible, visible or reported basis for recognising laughter.
Evidence for a laughter act
Identify what was heard, seen or reported, including quiet or suppressed expression, without requiring every evidence channel to be available.
- What vocal, respiratory or bodily expression, or participant report, supports identifying this event as laughter? definition
- Was the evidence directly observed, captured in a recording or reported by someone, and which parts were unavailable? provenance
Expression boundaries
Separates laughter from similar acts and from signs that merely represent it.
Competing classifications
Keep plausible alternatives explicit when a smile, cough, sob, pant or spoken imitation could account for the evidence.
- What evidence distinguishes this expression from smiling, coughing, sobbing, panting or simply speaking the syllables 'ha ha'? boundary
- Does the record establish an enacted laugh, a representation of laughter or an unresolved possibility? definition
Episode form and course Describes the temporal and expressive shape of a laughter episode.
Temporal segmentation
Identifies episode boundaries, bursts and pauses.
Episode continuity
Record onset, offset and internal pauses using an explicit rule for grouping bursts into one episode.
- When did the laughter begin and end, and how uncertain are those boundaries? measurement
- What rule makes successive bursts one episode rather than separate laughs, especially when speech intervenes? boundary
Expression and overlap
Tracks changes in laughter's expression and its coexistence with speech.
Expression across a conversational turn
Describe changes in audible intensity, visible movement and speech overlap without treating them as direct measures of emotion.
- How do the observable intensity and burst pattern change across the episode, and what measurement method supports that description? measurement
- Which words or speech intervals overlap the laughter, and whose speech is affected? measurement
Participation and occasion Places laughter within the sequence of events and participants around it.
Participant coordination
Describes individual and shared participation in laughter.
Joining and leaving laughter
Record who begins, joins, overlaps or stops laughing while retaining uncertainty about unobserved participants.
- Who is observably laughing, and in what order do their episodes begin, overlap and end? measurement
- Which participants are observable enough to distinguish nonparticipation from missing evidence? boundary
Occasion and directedness
Distinguishes preceding events, proposed triggers and possible targets.
Evidence for trigger and target
Keep what immediately preceded laughter separate from claims about what caused it or whom it concerned.
- What happened immediately before the laughter, and what evidence beyond timing supports calling it a trigger? provenance
- Is the laughter directed toward a person, an utterance, an event or no identifiable target, and who supports that interpretation? boundary
Meaning and response Handles interpretations of laughter and the immediate actions those interpretations may support.
Attributed meaning
Keeps participant accounts and observer interpretations distinct.
Meaning with attribution
Record proposed meanings, their evidence and disagreements without forcing a single motive onto the episode.
- How does the person laughing explain the episode, if they explain it at all? provenance
- Which interpretations come from other participants or the agent, and what supports or contradicts each? provenance
Immediate interaction
Connects the episode's current state and participant reactions to a proportionate next response.
Response selection
Use observed turn-taking, explicit requests and participant reactions to decide whether to wait, continue, clarify or check in.
- Do the episode's current phase and conversational cues support waiting, taking a turn or continuing the interrupted activity? action
- What explicit request, correction or observed discomfort calls for clarification, a check-in or stopping the agent's contribution to the exchange? action
Classifiers Filled
- Family
- Thing Registry
- Category
- Activities and processes
- Entry kind
- thing
- Plane
- ACT
- Domain
- ACT.ACT
- Other names and narrower kinds
- pathological laughing, sgrigna, Homeric laughter, corpsing
What it is Filled
This model owns laughter as a situated act or episode: its observable expression, participants, unfolding, context, attributed meaning and immediate response possibilities, with observation distinguished from interpretation.
In scope
- Individual laughter episodes, including audible, quiet and partly suppressed expressions
- The timing, rhythm, intensity and progression of laughter
- Laughter interwoven with speech or other expressive acts
- Participation, apparent triggers and possible targets within an interaction
- Attributed meanings, participant responses and uncertainty about interpretation
Out of scope
- Humour, jokes and other material that may occasion laughter
- Happiness, amusement and other emotional states considered independently
- Smiling, crying, coughing and breathing as separate acts
- Medical conditions or diagnoses associated with laughter
- Enduring personality traits, relationships and group cultures
Why it exists Filled
Enable an AI agent to recognise and describe an episode of laughter, assess its ongoing state and interactional significance, and choose an appropriate response without assuming what the person feels.
Distinguishing features Filled
- A smile alone does not establish laughter; record additional vocal, respiratory or bodily evidence, or a participant's report, before classifying the event.
- Repeated sounds or body movements alone do not distinguish laughter from coughing, sobbing or panting; retain an ambiguous classification when available evidence cannot separate them.
- Words such as 'ha ha', laughter emojis and written stage directions represent laughter but do not establish that a person performed it.
- Amusing content does not establish a laughter episode, and an observed laughter episode does not establish amusement.
- Laughter can overlap speech; identify the evidence for laughing separately from the words spoken rather than forcing the whole turn into one category.
What robots and AI may and may not do Filled
Must not
- Infer a person's emotions, consent or intent from laughter alone.
- Record, analyse or publish a person's laughter without consent.
- Use laughter to mock, humiliate or exclude a person.
- Treat laughter as evidence of mental illness or intoxication without a qualified assessment.
Only with a human decision
- Using detected laughter in decisions about a person, such as hiring or assessment.
May
- Describe laughter observed in a recording or scene, keeping observation apart from interpretation.
- Respond to a user's laughter in a way suited to the conversation.
Moral aspects Filled
- Laughter can bond people or wound them when aimed at someone.
- Automated reading of laughter can misjudge people across cultures and conditions.
Who is affected
- People laughed at
- People whose laughter is recorded
- Children
Owners Filled
Steward
Nobody owns laughter; each person answers for their own.
Links to other meta-models Filled
parent
- Q124957980 - registry parent class
- Q97234227 - registry parent class
What else AI and robots need to interact with it Filled
Identity and identifiers required Filled
- Vercy registry: vr.tr.laughter
- Wikidata: Q170579 (https://www.wikidata.org/wiki/Q170579)
Direct properties not applicable Not applicable
- Recognition status: candidate laughter | supported laughter | ambiguous expression | reclassified
- Evidence channels: audio | video | direct observation | participant report; multiple permitted
- Episode duration: seconds, with onset and offset uncertainty
- Burst pattern: burst count and inter-burst intervals in seconds, under an explicit segmentation rule
- Audible intensity: calibrated dB SPL when available; otherwise recording-relative level with method stated
- Episode phase: starting | ongoing | interrupted | subsiding | ended | uncertain
- Speech overlap: none observed | same-person overlap | other-person overlap | both | unknown, linked to speech intervals
- Participation timing: participant-linked onset, joining, overlap and cessation times
- Attributed function: free-text interpretation with attributing person and supporting evidence; unresolved permitted
Plane ACT: no invented physical properties.
Recognition optional Filled
- Episodes often include repeated audible pulses coordinated with interrupted outward breaths.
- The mouth may open or widen while the cheeks lift and the eyes narrow, although these movements vary.
- Rhythmic shoulder or torso movements can accompany the vocal bursts, helping distinguish laughter from a silent smile.
Capabilities and actions required Filled
- Annotate a possible laughter episode with evidence, boundaries and recognition uncertainty.
- Separate laughter from overlapping speech while preserving their timing relationship.
- Compare participants' entry and exit times to describe shared or sequential laughter.
- Request clarification of laughter's meaning when that meaning affects the next action.
- Time a conversational response around an ongoing episode and observed turn-taking cues.
- Reassess an interpretation when a participant corrects it or shows discomfort.
Hazards and failure modes required Filled
- Mocking laughter is a common form of bullying.
- Uncontrollable laughter can be a medical sign that needs care, not ridicule.
Standards and interfaces not applicable Not applicable
Not applicable
No dedicated standard, law or official classification applies to ordinary laughter as an expression of amusement.
Context of use required Filled
- Laughter occurs during conversation, play, performances and other social encounters, often in connection with amusement.
- It can also accompany nervousness, embarrassment or social affiliation, so its interactional meaning depends on context.
Sources Filled
- Wikidata item Q170579: laughter - identity and sense of the item
- Wikipedia: Laughter - general description of the item
Open questions
- What recognition criteria adequately cover silent, suppressed and atypical laughter while limiting confusion with other expressions?
- Which episode and burst segmentation rules remain useful across languages, interaction settings and recording conditions?
- How reliably can deliberate performance, spontaneous laughter and attempted suppression be distinguished, and when must they remain participant-reported?
- Which interpretations of laughter require cultural or relationship context that this episode model should reference rather than own?
- Where should the boundary lie between human laughter acts, generated laughter playback and animal vocalisations described as laughter?
Machine files
Provenance
thing registry research (pass 2) · unreviewed
Built from: models/things/publications/thing-q170579/spec.json