Identifying prompts used for training of inference models
US-2024273300-A1 · Aug 15, 2024 · US
US9514744B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9514744-B2 |
| Application number | US-201313964419-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 12, 2013 |
| Priority date | Feb 22, 2013 |
| Publication date | Dec 6, 2016 |
| Grant date | Dec 6, 2016 |
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Techniques for conversion of non-back-off language models for use in speech decoders. For example, an apparatus for conversion of non-back-off language models for use in speech decoders. For example, an apparatus is configured convert a non-back-off language model to a back-off language model. The converted back-off language model is pruned. The converted back-off language model is usable for decoding speech.
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What is claimed is: 1. An apparatus, comprising: a memory; and a processor coupled to the memory, forming at least one speech decoder, and configured to: convert a non-back-off language model to a back-off language model using a background language model, wherein the non-back-off language model assigns a probability to any fixed order n-gram without backing off to lower order n-gram probabilities, and wherein the background language model assigns a non-zero probability to n-gra…
Physics · mapped topic
Physics · mapped topic
Physics · mapped topic
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