Natural Language Processing (NLP) Performance Measure

A Natural Language Generation (NLG) Performance Measure is a linguistic processing performance measure for an NLG task (and NLG system).

AKA: NLG Evaluation Metric, NLG Quality Measure, Language Generation Performance Metric.
Context:
- It can typically be referenced by an NLG Performance Evaluation Task.
- It can typically assess NLG Text Fluency through NLG fluency metrics.
- It can typically evaluate NLG Text Coherence through NLG coherence analysises.
- It can typically measure NLG Factual Accuracy through NLG fact-checking metrics.
- It can typically determine NLG Text Relevance through NLG relevance scorings.
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- It can often support NLG System Improvement through NLG performance feedback.
- It can often enable NLG Model Comparison through NLG benchmark scorings.
- It can often facilitate NLG Quality Control through NLG threshold settings.
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- It can range from being an Intrinsic NLG Performance Measure to being an Extrinsic NLG Performance Measure, depending on its NLG evaluation context.
- It can range from being a Written NLG Performance Measure to being a Spoken NLG Performance Measure, depending on its NLG output modality.
- It can range from being a Manual NLG Performance Measure to being an Automated NLG Performance Measure, depending on its NLG evaluation methodology.
- It can range from being an Objective NLG Performance Measure to being a Subjective NLG Performance Measure, depending on its NLG measurement approach.
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- It can integrate NLG Reference Comparison with NLG human judgments.
- It can combine NLG Automatic Scoring with NLG linguistic analysises.
- It can support NLG Research Tasks through NLG experimental validations.
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Example(s):
- NLG Text Generation Performance Measures, such as:
  - NLG Fluency Measures for NLG text naturalness.
  - NLG Coherence Measures for NLG text structure.
- NLG Task-Specific Performance Measures, such as:
- Named NLG Performance Measures, such as:
  - BLEU Score for NLG translation quality.
  - ROUGE Score for NLG summarization quality.
  - METEOR Score for NLG synonym handling.
  - CIDEr Score for NLG image captioning.
  - Perplexity Measure for NLG language model evaluation.
  - BERTScore for NLG semantic similarity.
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Counter-Example(s):
- NLU Performance Measures, which evaluate natural language understanding tasks rather than NLG output quality.
- Information Retrieval Performance Measures, which assess search tasks rather than NLG text generation.
- Software Performance Measures, which evaluate software execution metrics rather than NLG linguistic quality.
See: Natural Language Generation, Text Summarization, Machine Translation, Language Model, Language Understanding Performance, Controlled-English Generation Task.