aisak-ai
/

aisak-stt

Automatic Speech Recognition

Safetensors

whisper

audio

speech-to-text

Model card Files Files and versions Community

mandelakori commited on 26 days ago

Commit

3eb569c

•

1 Parent(s): f17107f

Update README.md

Browse files

Files changed (1) hide show

README.md +132 -176

README.md CHANGED Viewed

@@ -1,199 +1,155 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## 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:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-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]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+language:
+- en
+- zh
+- de
+- es
+- ru
+- ko
+- fr
+- ja
+- pt
+- tr
+- pl
+- ca
+- nl
+- ar
+- sv
+- it
+- id
+- hi
+- fi
+- vi
+- he
+- uk
+- el
+- ms
+- cs
+- ro
+- da
+- hu
+- ta
+- no
+- th
+- ur
+- hr
+- bg
+- lt
+- la
+- mi
+- ml
+- cy
+- sk
+- te
+- fa
+- lv
+- bn
+- sr
+- az
+- sl
+- kn
+- et
+- mk
+- br
+- eu
+- is
+- hy
+- ne
+- mn
+- bs
+- kk
+- sq
+- sw
+- gl
+- mr
+- pa
+- si
+- km
+- sn
+- yo
+- so
+- af
+- oc
+- ka
+- be
+- tg
+- sd
+- gu
+- am
+- yi
+- lo
+- uz
+- fo
+- ht
+- ps
+- tk
+- nn
+- mt
+- sa
+- lb
+- my
+- bo
+- tl
+- mg
+- as
+- tt
+- haw
+- ln
+- ha
+- ba
+- jw
+- su
+tags:
+- audio
+- automatic-speech-recognition
+- speech-to-text
+pipeline_tag: automatic-speech-recognition
+license: other
+license_name: all-rights-reserved
 ---
+# AISAK-Listen
+### Overview:
+AISAK, short for Artificially Intelligent Swiss Army Knife, is a general-purpose AI system comprising various models designed for different tasks. Developed by the AISAK team, one of the models within AISAK is a state-of-the-art automatic speech recognition (ASR) model. This model, named AISAK-Listen, is fine-tuned on extensive datasets to excel in converting spoken language into written text.
+### Model Information:
+- **Model Name**: AISAK-Listen
+- **Version**: 1.0
+- **Model Architecture**: Seq2seq
+- **Specialization**: AISAK-Listen is a dedicated ASR model within the AISAK system, built off the impressive https://huggingface.co/openai/whisper-tiny model architecture. It has been fine-tuned to optimize performance for quick speech recognition tasks.
+### Intended Use:
+AISAK-Listen, as part of AISAK, is developed to provide reliable and high-quality speech-to-text conversion capabilities. It is intended to be a versatile tool for various applications such as transcription services, voice assistants, voice-controlled systems, and more. AISAK-Listen excels in accurately transcribing quick speech with minimal delay, making it suitable for real-time speech recognition requirements.
+### Performance:
+AISAK-Listen has undergone extensive testing to ensure its performance meets demanding standards. It consistently achieves impressive accuracy rates in converting spoken language to written text, outperforming other ASR models in terms of speed and efficiency. The model's performance has been evaluated on diverse speech datasets to ensure its generalization across different speakers and speech patterns.
+### Ethical Considerations:
+- **Bias Mitigation**: AISAK-Listen undergoes training processes that aim to minimize bias. However, it is important to note that biases may still be present in the transcriptions generated by the model.
+- **Fair Use**: Users are advised to exercise caution when utilizing AISAK-Listen in sensitive or critical contexts. The generated transcriptions should be reviewed and verified to ensure their accuracy and fairness.
+### Limitations:
+- AISAK-Listen's performance is optimized for quick speech recognition and may not be as effective for specialized speech styles or accents.
+- The model's accuracy may vary when exposed to speech data that significantly differs from the quick speech it was trained on.
+### Deployment:
+Inferencing for AISAK-Listen will be handled as part of the full deployment of the AISAK system in the future. The process is lengthy and intensive in many areas, emphasizing the goal of achieving the optimal system rather than the quickest. However, work is being done as fast as humanly possible. Updates will be provided as frequently as possible.
+### Caveats:
+- It is recommended to review and validate the transcriptions generated by AISAK-Listen, particularly in critical or high-stakes situations where accuracy is crucial.
+**Contact Information**: For any inquiries or communication regarding AISAK, please contact me at [email protected].
+**© 2024 Mandela Logan. All rights reserved.**
+No part of this model may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the copyright holder. Users are expressly prohibited from creating replications or spaces derived from this model, whether in whole or in part, without the explicit authorization of the copyright holder. Unauthorized use or reproduction of this model is strictly prohibited by copyright law.