US 10,311,144 B2Granted

Emoji word sense disambiguation

AssigneeApple Inc.

InventorsJerome R. Bellegarda, Bishal Barman

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Abstract

The present disclosure generally relates to systems and processes for emoji word sense disambiguation. In one example process, a word sequence is received. A word-level feature representation is determined for each word of the word sequence and a global semantic representation for the word sequence is determined. For a first word of the word sequence, an attention coefficient is determined based on a congruence between the word-level feature representation of the first word and the global semantic representation for the word sequence. The word-level feature representation of the first word is adjusted based on the attention coefficient. An emoji likelihood is determined based on the adjusted word-level feature representation of the first word. In accordance with the emoji likelihood satisfying one or more criteria, an emoji character corresponding to the first word is presented for display.

Claims48

Dependent claims

An electronic device, comprising:

one or more processors;
and
memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for:
receiving natural language input comprising a word sequence;
for each respective word of the word sequence, determining a feature representation of the respective word based on a left word context for the respective word and the right word context for the respective word;
determining a global semantic representation for the word sequence based on the left word context and the right word context for each respective word of the word sequence;
and
for each respective word of the word sequence that corresponds to a predefined word of a predefined emoji character:
determining a respective attention coefficient based on a congruence between the feature representation of the respective word of the word sequence and the global semantic representation for the word sequence;
adjusting the feature representation of the respective word of the word sequence based on the determined respective attention coefficient;
determining a respective emoji likelihood based on the adjusted feature representation of the respective word of the word sequence;
and
in accordance with the respective emoji likelihood satisfying one or more criteria, causing an emoji character corresponding to the respective word of the word sequence to be presented for display.

10 more elements

A method for emoji word sense disambiguation, the method comprising:

at an electronic device:
receiving natural language input comprising a word sequence;
for each respective word of the word sequence, determining a feature representation of the respective word based on a left word context for the respective word and the right word context for the respective word;
determining a global semantic representation for the word sequence based on the left word context and the right word context for each respective word of the word sequence;
and
for each respective word of the word sequence that corresponds to a predefined word of a predefined emoji character:
determining a respective attention coefficient based on a congruence between the feature representation of the respective word of the word sequence and the global semantic representation for the word sequence;
adjusting the feature representation of the respective word of the word sequence based on the determined respective attention coefficient;
determining a respective emoji likelihood based on the adjusted feature representation of the respective word of the word sequence;
and
in accordance with the respective emoji likelihood satisfying one or more criteria, causing an emoji character corresponding to the respective word of the word sequence to be presented for display.

8 more elements

A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of an electronic device with a display and memory, the one or more programs including instructions for:

receiving natural language input comprising a word sequence;
for each respective word of the word sequence, determining a feature representation of the respective word based on a left word context for the respective word and the right word context for the respective word;
determining a global semantic representation for the word sequence based on the left word context and the right word context for each respective word of the word sequence;
and
for each respective word of the word sequence that corresponds to a predefined word of a predefined emoji character:
determining a respective attention coefficient based on a congruence between the feature representation of the respective word of the word sequence and the global semantic representation for the word sequence;
adjusting the feature representation of the respective word of the word sequence based on the determined respective attention coefficient;
determining a respective emoji likelihood based on the adjusted feature representation of the respective word of the word sequence;
and
in accordance with the respective emoji likelihood satisfying one or more criteria, causing an emoji character corresponding to the respective word of the word sequence to be presented for display.

7 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/678,618Filed 16 Aug 2017 · us provisional application
Priority: 16 May 2017
Published: US 2018/0336184 A122 Nov 2018
Granted: 4 Jun 2019
Term ends: Not estimatedThe source records don’t support an estimate.

Classification4 codes

G06F 40/30
Handling natural language data: semantic analysis
G06F 3/0237
Character input methods: using prediction or retrieval techniques
G06F 3/04817
Based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like…:…
G06F
Computing and data processing

Family

Application62/506,989Us provisional application · filed 16 May 2017
US 2018/0336184 A1Pre-grant publication · published 22 Nov 2018
US 10,311,144 B2This patent

From the US filing history. Foreign family members aren’t listed.

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