69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
import time
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import azure.cognitiveservices.speech as speechsdk
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from core import tts_voice
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from core.tts_voice import EnumVoice
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from utils import util, config_util
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from utils import config_util as cfg
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class Speech:
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def __init__(self):
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self.__speech_config = speechsdk.SpeechConfig(subscription=cfg.key_ms_tts_key, region="eastasia")
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self.__speech_config.speech_recognition_language = "zh-CN"
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self.__speech_config.speech_synthesis_voice_name = "zh-CN-XiaoxiaoNeural"
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self.__speech_config.set_speech_synthesis_output_format(speechsdk.SpeechSynthesisOutputFormat.Audio16Khz32KBitRateMonoMp3)
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self.__synthesizer = speechsdk.SpeechSynthesizer(speech_config=self.__speech_config, audio_config=None)
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self.__connection = None
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self.__history_data = []
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def __get_history(self, voice_name, style, text):
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for data in self.__history_data:
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if data[0] == voice_name and data[1] == style and data[2] == text:
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return data[3]
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return None
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def connect(self):
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self.__connection = speechsdk.Connection.from_speech_synthesizer(self.__synthesizer)
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self.__connection.open(True)
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util.log(1, "TTS 服务已经连接！")
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def close(self):
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if self.__connection is not None:
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self.__connection.close()
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"""
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文字转语音
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:param text: 文本信息
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:param style: 说话风格、语气
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:returns: 音频文件路径
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"""
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def to_sample(self, text, style):
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voice_type = tts_voice.get_voice_of(config_util.config["attribute"]["voice"])
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voice_name = EnumVoice.XIAO_XIAO.value["voiceName"]
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if voice_type is not None:
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voice_name = voice_type.value["voiceName"]
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history = self.__get_history(voice_name, style, text)
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if history is not None:
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return history
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ssml = '<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xmlns:mstts="https://www.w3.org/2001/mstts" xml:lang="zh-CN">' \
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'<voice name="{}">' \
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'<mstts:express-as style="{}" styledegree="{}">' \
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'{}' \
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'</mstts:express-as>' \
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'</voice>' \
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'</speak>'.format(voice_name, style, 1.8, text)
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result = self.__synthesizer.speak_ssml(ssml)
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audio_data_stream = speechsdk.AudioDataStream(result)
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file_url = './samples/sample-' + str(int(time.time() * 1000)) + '.mp3'
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audio_data_stream.save_to_wav_file(file_url)
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if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
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self.__history_data.append((voice_name, style, text, file_url))
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return file_url
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else:
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util.log(1, "[x] 语音转换失败！")
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util.log(1, "[x] 原因: " + str(result.reason))
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return None
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