Scalable backoff language models
Explore this paper's citation graph
- Type
- article
- Published
- 1996-10-03
- Cited by
- 108
- References
- 7
- Access
- Open access
- OpenAlex
- https://openalex.org/W1903115690
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9379111
Keywords
Bigram, Trigram, Perplexity, Language model, Computer science
References
- Optimizing lexical and N-gram coverage via judicious use of linguistic data
- Estimation of probabilities from sparse data for the language model component of a speech recognizer
- The CMU Statistical Language Modeling Toolkit and its use in the 1994 ARPA CSR Evaluation
- Scalable Trigram Backoff Language Models
- Optimizing Lexical and Ngram Coverage via Judicious Use of Linguistic Data
- Self-organized language modeling for speech recognition
- -organized Language Modeling for Speech Recognition". In
Cited by
- Language models for automatic speech recognition : construction and complexity control
- On Cross-lingual Plagiarism Analysis using a Statistical Model
- Language model size reduction by pruning and clustering
- Multimodal intent recognition for natural human-robotic interaction
- Study on interaction between entropy pruning and kneser-ney smoothing
- The Juicer LVCSR Decoder - User Manual for Juicer version 0.5.0
- The Use of Clustering Techniques for Language Modeling V Application to Asian Language
- Compressing Trigram Language Models With Golomb Coding
- The AT&t large vocabulary conversational speech recognition system
- Morfessor and variKN machine learning tools for speech and language technology
- Spoken Content-Based Audio Navigation (SCAN)
- A comparison of two LVR search optimization techniques
- WFST compression for automatic speech recognition
- Fast vocabulary-independent audio search using path-based graph indexing
- Corpus Variation and Parser Performance
- Detecting Fake Content with Relative Entropy Scoring
- Improving Translation Selection with a New Translation Model Trained by Independent Monolingual Corpora
- Improving Relative-Entropy Pruning using Statistical Significance
- Statistical language understanding using frame semantics
- A method to build a super small but practically accurate language model for handheld devices
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