# 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.