Statistical continuous speech recognizer
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Massachusetts Institute of Technology (MIT)
- Organisation type
- Academia
- Country
- United States of America
- Published
- 30 April 1976
- Authors
- Frederick Jelenick
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Speech
- Task
- Speech recognition (ASR)
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 12,000 tokens
800 sentences, counting 15 words per sentence gives 12000 words "All the results given are for a training set of 800 sentences and a test set of 100 sentences"
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 1,591
Sources
Where this record came from and when it was last checked.
- Reference
- Continuous speech recognition by statistical methods
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Statistical continuous speech recognizer was published by Massachusetts Institute of Technology (MIT), in the country recorded as United States of America, during April 1976. It comes out of an organisation categorised as academia.
It works in the domain of Speech, and is recorded as performing the task of speech recognition (ASR).
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
It was trained on a corpus of about 12,000 tokens of text.
Answers
Statistical continuous speech recognizer — common questions
Statistical continuous speech recognizer— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Statistical continuous speech recognizer— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Statistical continuous speech recognizer— who created it?
It was published by Massachusetts Institute of Technology (MIT), based in United States of America, an organisation categorised as academia.
Statistical continuous speech recognizer— when was it released?
It was published in April 1976. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Statistical continuous speech recognizer— what is it used for?
It works in the domain of Speech, and is recorded as handling the task of speech recognition (ASR). These are the areas it was designed around; they describe intent rather than a hard boundary.
Statistical continuous speech recognizer— what GPU do I need to run it?
None. This is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.