Zen3 Audio
Collection
Speech recognition + text-to-speech. • 7 items • Updated
How to use zenlm/zen3-asr-aligner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="zenlm/zen3-asr-aligner") # Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("zenlm/zen3-asr-aligner")
model = AutoModelForMultimodalLM.from_pretrained("zenlm/zen3-asr-aligner")Forced-alignment companion to Zen3 ASR. Produces word- and phoneme-level time alignments for transcripts (subtitle sync, dataset curation, dubbing). The config declares support for 11 languages.
Derived by fine-tuning Qwen/Qwen3-ForcedAligner-0.6B (Alibaba Cloud, Apache-2.0).
Qwen3ASRForConditionalGeneration (qwen3_asr)Qwen/Qwen3-ForcedAligner-0.6BThis repository contains the model weights: model.safetensors, config and tokenizer files.
The model uses the qwen3_asr architecture and loads with transformers (>= 4.57). It is API-compatible with the upstream base — follow the inference recipe on the base model card Qwen/Qwen3-ForcedAligner-0.6B.
Fine-tuned from Qwen/Qwen3-ForcedAligner-0.6B (Apache-2.0). See NOTICE for full attribution.
Base model
Qwen/Qwen3-ForcedAligner-0.6B