# Automatic Speech Recognition Advancements for Indigenous Languages of the Americas
## 6 Data and Models Accessibility  
The data utilized for fine-tuning, provided by the AmericasNLP challenge, are accessible online [88]. The results obtained by performing experiments with different hyperparameters and configurations are available in the Supplementary Information (SI). The fine-tuned models for each language, including Quechua, Bribri, Kotiria, Guarani, and Wa'ikhana, are accessible online [88]. The models can be accessed at the following URLs:  
* Quechua ([[https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-quechua]([https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-quechua)) (accessed on 12 September 2023)
* Kotiria ([[https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-kotiria]([https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-kotiria)) (accessed on 12 September 2023)
* Wa'ikhana ([[https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-waikhana]([https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-waikhana)) (accessed on 12 September 2023)
* Guarani ([[https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-guarani]([https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-guarani)) (accessed on 12 September 2023)
* Bribri ([[https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-bribri]([https://huggingface.co/ivangtorre/wav2](https://huggingface.co/ivangtorre/wav2) vec2-xlsr-300m-bribri)) (accessed on 12 September 2023).  
Scripts prepared for downloading the fine-tuned models and performing inference are now available at [[https://github.com/monirrome/asr-indigenous-languages](https://github.com/monirrome/asr-indigenous-languages)]([https://github.com/monirrome/asr-indigenous-languages](https://github.com/monirrome/asr-indigenous-languages)) (accessed on 12 September 2023) [88].  
**Supplementary Materials:** The following supporting information can be downloaded at: www.mdpi.com/xxx/s1. Table S1: Detailed fine-tuning results for the Quechua ASR model, illustrating WER variations based on hyperparameter configuration. Table S2. Detailed fine-tuning results for the Kotiria ASR model, illustrating WER variations based on hyperparameter configuration. Table S3. Detailed fine-tuning results for the Bribri ASR model, illustrating WER variations based on hyperparameter configuration. Table S4. Detailed fine-tuning results for the Guarani ASR model, illustrating WER variations based on hyperparameter configuration. Table S5. Detailed fine-tuning results for the Wai'khana ASR model, illustrating WER variations based on hyperparameter configuration.  
**Author Contributions:** Conceptualization, I.G.T.; Methodology, I.G.T.; Software, M.R.; Investigation, M.R. and I.G.T.; Resources, M.R.; Data curation, M.R.; Writing--original draft, M.R. and I.G.T.; Writing--review & editing, M.R., S.G.-C. and I.G.T.; Supervision, S.G.-C. and I.G.T.; Funding acquisition, S.G.-C. All authors have read and agreed to the published version of the manuscript.  
Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors. Acknowledgments: The authors gratefully acknowledge the Universidad Politecnica de Madrid for providing computing resources on the Magerit Supercomputer. Conflicts of Interest: The authors declare no conflicts of interest. References