This repository contains audio.cpp-native GGUF builds of `microsoft/VibeVoice-ASR-Streaming-1.5B`. The 1.5B checkpoint runs through the same audio.cpp loader as the 7B with no code changes: the layer count, hidden size, and head counts are read from the checkpoint's own `config.json`, and the tensor names are identical. Each GGUF is self-contained and embeds the audio.cpp package spec and required sidecars.

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whisperfile

cjpais

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

基本情報を収録・詳細は順次追加

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cohere-asr-ja-GGUF

CKHO

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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wav2vec2-xls-r-juznevesti-sr

classla

This model for Serbian ASR is based on the facebook/wav2vec2-xls-r-300m model and was fine-tuned with 58 hours of audio and transcripts from Južne vesti, programme '15 minuta'. For more info on the dataset creation see this repo. Tested with `transformers==4.18.0`, `torch==1.11.0`, and `SoundFile==0.10.3.post1`.

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wav2vec2-french-phonemizer

Cnam-LMSSC

Fine-tuned facebook/wav2vec2-base-fr-voxpopuli-v2 for **French speech-to-phoneme** (without language model) using the train and validation splits of Common Voice v13. As this model is specifically trained for a speech-to-phoneme task, the output is sequence of IPA-encoded words, without punctuation. If you don't read the phonetic alphabet fluently, you can use this excellent IPA reader website to convert the transcript back to audio synthetic speech in order to check the quality of the phonetic transcription. The model has been finetuned on Commonvoice-v13 (FR) for 14 epochs on a 4x2080 Ti GPUs at Cnam/LMSSC using a ddp strategy and gradient-accumulation procedure (256 audios per update, corresponding roughly to 25 minutes of speech per update -> 2k updates per epoch)

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wav2vec2-french-phonemizer-v2

Cnam-LMSSC

This version fixes the absence of the voiced labial-palatal approximant **ɥ**. The original Cnam-LMSSC/wav2vec2-french-phonemizer never transcribes the pronunciation of the voiced labial–palatal approximant with /ɥ/ and instead incorrectly replaces it with the sequence /yi/. This created issues for phonetic accuracy and linguistic analysis. Words like "nuit" or "huit" are pronounced with \ɥ\ and not with \yi\ For Text-to-Speech (TTS) task, substituting \ɥ\ with \yi\ results in unnatural prosody. Fine-tuned facebook/wav2vec2-base-fr-voxpopuli-v2 for **French speech-to-phoneme** (without language model) using the train and validation splits of Common Voice v13. As this model is specifically trained for a speech-to-phoneme task, the output is sequence of IPA-encoded words, without punctuation. If you don't read the phonetic alphabet fluently, you can use this excellent IPA reader website to convert the transcript back to audio synthetic speech in order to check the quality of the phonetic transcription.

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