Audio Classification
LiteRT
LiteRT
language-identification
language-detection
langid
spoken-language-identification
speech
on-device
edge-ai
mobile
offline
core-ml
apple-neural-engine
multilingual
Instructions to use desert-ant-labs/ear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use desert-ant-labs/ear with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Third-party notices
openai/whisper-tiny
The weights in this repository are derived from
openai/whisper-tiny, released by
OpenAI under the MIT License. The derivation removes the parameters this task
does not use, keeps the subgraph that predicts a language, and compresses the
result for on-device execution.
MIT License
Copyright (c) 2022 OpenAI
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Evaluation corpora
Published accuracy figures are measured on FLEURS (CC BY 4.0, Google) and VoxPopuli (CC0, Meta). Neither corpus is redistributed here.