| # Things that might be relevant | |
| ## Trained models | |
| ESPnet model for Yoloxochitl Mixtec | |
| - Huggingface Hub page https://huggingface.co/espnet/ftshijt_espnet2_asr_yolo_mixtec_transformer | |
| - Model source code https://github.com/espnet/espnet/tree/master/egs/yoloxochitl_mixtec/asr1 | |
| - Colab notebook to setup and apply the model https://colab.research.google.com/drive/1ieoW2b3ERydjaaWuhVPBP_v2QqqWsC1Q?usp=sharing | |
| Coqui model for Yoloxochitl Mixtec | |
| - Huggingface Hub page | |
| - Coqui page https://coqui.ai/mixtec/jemeyer/v1.0.0 | |
| - Colab notebook to setup and apply the model https://colab.research.google.com/drive/1b1SujEGC_F3XhvUCuUyZK_tyUkEaFZ7D?usp=sharing#scrollTo=6IvRFke4Ckpz | |
| Spanish ASR models | |
| - XLS-R model based on CV8 with LM https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-spanish | |
| - XLSR model based on CV6 with LM https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-spanish | |
| - XLSR model based on Librispeech https://huggingface.co/IIC/wav2vec2-spanish-multilibrispeech | |
| Speechbrain Language identification on Common Language (from Common Voice 6/7?) | |
| - source code https://github.com/speechbrain/speechbrain/tree/develop/recipes/CommonLanguage | |
| - HF Hub model page https://huggingface.co/speechbrain/lang-id-commonlanguage_ecapa | |
| - HF Hub space https://huggingface.co/spaces/akhaliq/Speechbrain-audio-classification | |
| Speechbrain Language identification on VoxLingua | |
| - source code https://github.com/speechbrain/speechbrain/tree/develop/recipes/VoxLingua107/lang_id | |
| - HF Hub model page https://huggingface.co/speechbrain/lang-id-voxlingua107-ecapa | |
| ## Corpora | |
| OpenSLR89 https://www.openslr.org/89/ | |
| Common Language https://huggingface.co/datasets/common_language | |
| VoxLingua http://bark.phon.ioc.ee/voxlingua107/ | |
| Multilibrispeech https://huggingface.co/datasets/multilingual_librispeech | |
| # Possible demos | |
| ## Simple categorization of utterances | |
| A few example files are provided for each language, and the user can record their own. | |
| The predicted confidence of each class label is shown. | |
| ## Segmentation and identification | |
| Recordings with alternating languages in a single audio file, provided examples or the user can record. | |
| Some voice activity detection to split the audio, then predict language of each piece | |
| ## Identication and transcription | |
| Example files for each language separately. | |
| The lang-id model predicts what language it is. | |
| The corresponding ASR model produces a transcript. | |
| ## Segmentation, identification and transcription | |
| Recordings with alternating languages in a single audio file. | |
| Use voice activity detection to split the audio, then predict the language of each piece | |
| Use the corresponding ASR model to produce a transcript of each piece to display. |