transcribe-monkey / README.md
jdalegonzalez's picture
Update README.md
2d2e4ad verified
|
raw
history blame
4.66 kB
---
library_name: transformers
language:
- en
- zh
base_model:
- superb/wav2vec2-base-superb-sid
---
# Model Card for Model ID
The model is intended to speaker identification for audio segments taken from the Mandarin Monkey podcast.
It was created based the speakerbox code. https://councildataproject.org/speakerbox/
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** jdalegonzalez
- **Funded by [optional]:** None. sigh
- **Model type:** Wave2Vec audio classifier
- **Language(s) (NLP):** English and Chinese
- **License:** Meh?
- **Finetuned from model:** superb/wav2vec2-base-superb-sid
## Uses
Right now, the only thing the model will do is identify which speaker (between the two hosts of Mandarin Monkey)
is likely speaking a specific audio clip. In the future, it could be expanded to support
more speakers, more podcasts, etc...
### Direct Use
I'm not sure what direct use is possible other than diarizing a Mandarin Monkey podcast.
[More Information Needed]
### Out-of-Scope Use
Really, almost any use other than identifying which host is speaking a particular
audio clip is out-of-scope.
[More Information Needed]
## Bias, Risks, and Limitations
There is no warranty expressed or implied. It works for me. It may do
nothing for you. This is experimental and shouldn't be the basis
for any commericial activity.
[More Information Needed]
### Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]