Paper Title:
IMPROVING LANGUAGE MODEL SIZE REDUCTION USING BETTER PRUNING CRITERIA
IMPROVING LANGUAGE MODEL SIZE REDUCTION USING BETTER PRUNING CRITERIA
Authors: Jianfeng Gao and Min Zhang
Primarily assigned technology terms:
- algorithm
- bigram model pruning
- bigram model training
- bigram pruning
- computational linguistics
- cutoff
- cutoff pruning
- decoder
- decoding
- learning
- likelihood estimation
- linear regression
- lm pruning
- loss function
- maximum likelihood
- maximum likelihood estimation
- model pruning
- model size reduction
- model training
- normalization
- pruning
- pruning method
- recognition
- recognition system
- regression
- search
- smoothing
- smoothing method
- speech recognition
- speech recognition system
- thresholding
- thresholding pruning
Other assigned terms:
- alphabet
- ambiguity
- backoff
- backoff n-gram model
- bigram
- bigram model
- character error rate
- characters
- chinese characters
- chinese text
- coefficient
- comparative study
- conditional probabilities
- conditional probability
- corpora
- correlation
- correlation coefficient
- data sparseness
- distribution
- document
- entropy
- error rate
- estimation
- evaluation measure
- evaluation measures
- experimental results
- fact
- finite set
- hypothesis
- kullback-leibler divergence
- language model
- language model probability
- language models
- lexicon
- likelihood
- linear regression model
- linguistics
- measure
- measures
- method
- model perplexity
- model probability
- model size
- n-gram
- n-gram model
- n-gram models
- normalization factor
- ordered list
- perplexity
- phonetic alphabet
- pinyin
- probabilities
- probability
- probability distribution
- probability estimate
- pruning bigram
- pruning threshold
- rank-order correlation coefficient
- regression model
- search space
- style
- target word
- terms
- test corpora
- test data
- test set
- text
- training
- training data
- transcript
- trigram
- unigram
- vocabulary
- vocabulary size
- word
- word error rate
- word pair
- word string
- word strings
- words
Extracted Section Types:
This page last edited on 06 October 2025.



