txya900619
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Parent(s):
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feat: upload app.py and needed file
Browse files- DEMO.md +17 -0
- app.py +134 -0
- configs/models.yaml +12 -0
- requirements.txt +2 -0
DEMO.md
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# 原語會族語語音辨識系統
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ILRDF Formosan Automatic-Speech-Recognition System
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## 研發團隊
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- [李鴻欣 Hung-Shin Lee](mailto:hungshinlee@gmail.com)
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- [陳力瑋 Li-Wei Chen](mailto:wayne900619@gmail.com)
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- [意傳科技](https://ithuan.tw/)
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- [原住民族語言研究發展基金會](https://www.ilrdf.org.tw/)
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## 特別致謝
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- [聯和科創](https://www.104.com.tw/company/1a2x6bmu75)
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- [台灣阿美族語言永續發展學會/原民會阿美族語言推動組織](https://www.facebook.com/groups/ypspt/about)
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- [台灣太魯閣族語言發展學會](https://qkktt.com/)
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- [台灣原住民族賽德克族語言文化學會](https://www.facebook.com/3S3TBL/)
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- 族語老師們
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app.py
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import json
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import gradio as gr
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from huggingface_hub import snapshot_download
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from omegaconf import OmegaConf
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from vosk import KaldiRecognizer, Model
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def load_vosk(model_id: str):
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model_dir = snapshot_download(model_id)
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return Model(model_path=model_dir)
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OmegaConf.register_new_resolver("load_vosk", load_vosk)
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models_config = OmegaConf.to_object(OmegaConf.load("configs/models.yaml"))
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def automatic_speech_recognition(model_id: str, dialect_id: str, audio_data: str):
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if isinstance(models_config[model_id]["model"], dict):
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model = models_config[model_id]["model"][dialect_id]
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else:
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model = models_config[model_id]["model"]
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sample_rate, audio_array = audio_data
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if audio_array.ndim == 2:
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audio_array = audio_array[:, 0]
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audio_bytes = audio_array.tobytes()
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rec = KaldiRecognizer(model, sample_rate)
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rec.SetWords(True)
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results = []
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for start in range(0, len(audio_bytes), 4000):
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end = min(start + 4000, len(audio_bytes))
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data = audio_bytes[start:end]
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if rec.AcceptWaveform(data):
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raw_result = json.loads(rec.Result())
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results.append(raw_result)
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final_result = json.loads(rec.FinalResult())
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results.append(final_result)
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filtered_lines = []
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for result in results:
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result["text"] = result["text"].replace(" ", "")
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if len(result["text"]) > 0:
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filtered_lines.append(result["text"])
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return ",".join(filtered_lines) + "。"
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def when_model_selected(model_id: str):
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model_config = models_config[model_id]
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if "dialect_mapping" not in model_config:
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return gr.update(visible=False)
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dialect_drop_down_choices = [
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(k, v) for k, v in model_config["dialect_mapping"].items()
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]
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return gr.update(
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choices=dialect_drop_down_choices,
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value=dialect_drop_down_choices[0][1],
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visible=True,
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)
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demo = gr.Blocks(
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title="臺灣南島語語音辨識系統",
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css="@import url(https://tauhu.tw/tauhu-oo.css);",
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theme=gr.themes.Default(
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font=(
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"tauhu-oo",
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gr.themes.GoogleFont("Source Sans Pro"),
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"ui-sans-serif",
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"system-ui",
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"sans-serif",
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)
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),
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)
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with demo:
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default_model_id = list(models_config.keys())[0]
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model_drop_down = gr.Dropdown(
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models_config.keys(),
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value=default_model_id,
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label="模型",
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)
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dialect_drop_down = gr.Radio(
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choices=[
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(k, v)
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for k, v in models_config[default_model_id]["dialect_mapping"].items()
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],
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value=list(models_config[default_model_id]["dialect_mapping"].values())[0],
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label="族別",
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)
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model_drop_down.input(
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when_model_selected,
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inputs=[model_drop_down],
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outputs=[dialect_drop_down],
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)
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with open("DEMO.md") as tong:
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gr.Markdown(tong.read())
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gr.Interface(
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automatic_speech_recognition,
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inputs=[
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model_drop_down,
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dialect_drop_down,
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gr.Audio(
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label="上傳或錄音",
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type="numpy",
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format="wav",
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waveform_options=gr.WaveformOptions(
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sample_rate=16000,
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),
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),
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],
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outputs=[
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gr.Text(interactive=False, label="客語漢字"),
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],
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allow_flagging="auto",
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)
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demo.launch()
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configs/models.yaml
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formosan-kaldi:
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model:
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formosan_ami: ${load_vosk:united-link/kaldi-formosan-ami}
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formosan_sdq: ${load_vosk:united-link/kaldi-formosan-sdq}
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formosan_trv: ${load_vosk:united-link/kaldi-formosan-trv}
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formosan_pwn: ${load_vosk:united-link/kaldi-formosan-pwn}
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dialect_mapping:
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阿美: formosan_ami
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賽德克: formosan_sdq
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太魯閣: formosan_trv
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排灣: formosan_pwn
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requirements.txt
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vosk
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omegaconf
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