Time-delay neural networks
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
- Advanced Telecommunications Research Institute,Carnegie Mellon University (CMU)
- Organisation type
- Industry,Academia
- Country
- Japan, United States of America
- Published
- 3 March 1989
- Authors
- A. Waibel, T. Hanazawa, G. Hinton, K. Shikano, and K. J. Lang
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
- 2,046 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 3,445
Sources
Where this record came from and when it was last checked.
- Reference
- Phoneme recognition using time-delay neural networks
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Time-delay neural networks was published by Advanced Telecommunications Research Institute,Carnegie Mellon University (CMU), in the country recorded as Japan, during March 1989. The publishing organisation is categorised as industry,Academia.
It works in the domain of Speech, and is recorded as performing the task of speech recognition (ASR).
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training set ran to roughly 2,046 tokens of text.
Answers
Time-delay neural networks — common questions
Time-delay neural networks— 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.
Time-delay neural networks— 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.
Time-delay neural networks— 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.
Time-delay neural networks— who created it?
It was published by Advanced Telecommunications Research Institute,Carnegie Mellon University (CMU), based in Japan, an organisation categorised as industry,Academia.
Time-delay neural networks— when was it released?
It was published in March 1989. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Time-delay neural networks— what is it used for?
It works in the domain of Speech, and is recorded as handling the task of speech recognition (ASR). A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
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.