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+ ---
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+ license: apache-2.0
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+ language:
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+ - ja
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+ - en
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+ library_name: transformers
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+ base_model: Qwen/Qwen3-ASR-1.7B
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+ pipeline_tag: automatic-speech-recognition
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+ tags:
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+ - automatic-speech-recognition
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+ - asr
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+ - japanese
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+ - qwen3-asr
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+ - speech
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+ - audio
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+ ---
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+
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+ # Japanese Proper-Noun Fine-tuned Qwen3-ASR
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+
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+ A fine-tuned checkpoint of [`Qwen/Qwen3-ASR-1.7B`](https://huggingface.co/Qwen/Qwen3-ASR-1.7B) optimized for Japanese automatic speech recognition.
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+
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+ This variant is specifically trained to improve recognition of Japanese proper nouns, organization names, product names, service names, and kanji-heavy expressions that general-purpose ASR models tend to mistranscribe.
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+
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+ ## Intended Use
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+
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+ Designed for Japanese ASR tasks requiring accurate transcription of:
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+
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+ - Proper nouns (people, places, organizations)
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+ - Difficult or uncommon kanji spellings
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+ - Company and product names
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+ - Mixed Japanese/English technical terminology
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+
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+ ### Example Normalizations
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+
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+ | Spoken (katakana) | Expected output |
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+ | ----------------- | --------------- |
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+ | ジェミニ | `Gemini` |
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+ | アンスロピック | `Anthropic` |
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+ | ノートブックLM | `NotebookLM` |
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+
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+ ## Model Details
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+
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+ | | |
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+ | --------------------- | -------------------------------------------- |
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+ | **Base model** | `Qwen/Qwen3-ASR-1.7B` |
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+ | **Task** | Automatic speech recognition |
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+ | **Language** | Japanese (ja), English (en) |
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+ | **Fine-tuning focus** | Japanese proper nouns & technical vocabulary |
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+
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+ ## Quickstart
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+
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+ Install the runtime package:
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+
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+ ```bash
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+ pip install -U qwen-asr
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+ ```
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+
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+ Transcribe a local audio file:
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+
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+ ```python
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+ import torch
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+ from qwen_asr import Qwen3ASRModel
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+
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+ model = Qwen3ASRModel.from_pretrained(
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+ "neosophie/Qwen3-ASR-1.7B-JA",
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+ dtype=torch.bfloat16,
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+ device_map="cuda:0",
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+ )
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+
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+ results = model.transcribe(audio="/path/to/audio.wav")
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+
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+ print(results[0].language)
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+ print(results[0].text)
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+ ```
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+
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+ ## Acknowledgments
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+
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+ - [Qwen3-ASR-1.7B](https://huggingface.co/Qwen/Qwen3-ASR-1.7B) — base model by Alibaba Cloud