mirror of
https://github.com/HiMeditator/auto-caption.git
synced 2026-02-04 03:46:11 +08:00
eba2c5ca45
- 重构字幕引擎，将音频采集改为在新线程上进行 - 重构 audio2text 中的类，调整运行逻辑 - 更新 main 函数，添加对 Sosv 模型的支持 - 修改 AudioStream 类，默认使用 16000Hz 采样率
118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
from dashscope.audio.asr import (
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TranslationRecognizerCallback,
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TranscriptionResult,
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TranslationResult,
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TranslationRecognizerRealtime
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)
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import dashscope
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from dashscope.common.error import InvalidParameter
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from datetime import datetime
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from utils import stdout_cmd, stdout_obj, stdout_err
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from utils import shared_data
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class Callback(TranslationRecognizerCallback):
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"""
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语音大模型流式传输回调对象
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"""
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def __init__(self):
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super().__init__()
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self.index = 0
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self.usage = 0
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self.cur_id = -1
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self.time_str = ''
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def on_open(self) -> None:
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self.usage = 0
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self.cur_id = -1
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self.time_str = ''
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stdout_cmd('info', 'Gummy translator started.')
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def on_close(self) -> None:
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stdout_cmd('info', 'Gummy translator closed.')
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stdout_cmd('usage', str(self.usage))
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def on_event(
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self,
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request_id,
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transcription_result: TranscriptionResult,
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translation_result: TranslationResult,
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usage
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) -> None:
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caption = {}
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if transcription_result is not None:
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if self.cur_id != transcription_result.sentence_id:
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self.time_str = datetime.now().strftime('%H:%M:%S.%f')[:-3]
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self.cur_id = transcription_result.sentence_id
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self.index += 1
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caption['command'] = 'caption'
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caption['index'] = self.index
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caption['time_s'] = self.time_str
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caption['time_t'] = datetime.now().strftime('%H:%M:%S.%f')[:-3]
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caption['text'] = transcription_result.text
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caption['translation'] = ""
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if translation_result is not None:
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lang = translation_result.get_language_list()[0]
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caption['translation'] = translation_result.get_translation(lang).text
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if usage:
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self.usage += usage['duration']
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if 'text' in caption:
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stdout_obj(caption)
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class GummyRecognizer:
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"""
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使用 Gummy 引擎流式处理的音频数据，并在标准输出中输出与 Auto Caption 软件可读取的 JSON 字符串数据
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初始化参数：
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rate: 音频采样率
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source: 源语言代码字符串（zh, en, ja 等）
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target: 目标语言代码字符串（zh, en, ja 等）
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api_key: 阿里云百炼平台 API KEY
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"""
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def __init__(self, rate: int, source: str, target: str | None, api_key: str | None):
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if api_key:
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dashscope.api_key = api_key
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self.translator = TranslationRecognizerRealtime(
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model = "gummy-realtime-v1",
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format = "pcm",
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sample_rate = rate,
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transcription_enabled = True,
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translation_enabled = (target is not None),
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source_language = source,
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translation_target_languages = [target],
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callback = Callback()
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)
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def start(self):
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"""启动 Gummy 引擎"""
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self.translator.start()
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def translate(self):
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"""持续读取共享数据中的音频帧，并进行语音识别，将识别结果输出到标准输出中"""
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global shared_data
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restart_count = 0
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while shared_data.status == 'running':
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chunk = shared_data.chunk_queue.get()
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try:
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self.translator.send_audio_frame(chunk)
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except InvalidParameter as e:
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restart_count += 1
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if restart_count > 5:
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stdout_err(str(e))
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shared_data.status = "kill"
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stdout_cmd('kill')
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break
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else:
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stdout_cmd('info', f'Gummy engine stopped, restart attempt: {restart_count}...')
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def stop(self):
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"""停止 Gummy 引擎"""
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try:
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self.translator.stop()
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except Exception:
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return
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