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https://github.com/RVC-Boss/GPT-SoVITS.git
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RVC-Boss
GitHub
commit
ed75ecdd6d
@ -576,22 +576,22 @@ class TTS:
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Args:
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inputs (dict):
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{
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"text": "", # str. text to be synthesized
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"text_lang: "", # str. language of the text to be synthesized
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"ref_audio_path": "", # str. reference audio path
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"prompt_text": "", # str. prompt text for the reference audio
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"prompt_lang": "", # str. language of the prompt text for the reference audio
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"top_k": 5, # int. top k sampling
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"top_p": 1, # float. top p sampling
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"temperature": 1, # float. temperature for sampling
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"text_split_method": "", # str. text split method, see text_segmentaion_method.py for details.
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"batch_size": 1, # int. batch size for inference
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"batch_threshold": 0.75, # float. threshold for batch splitting.
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"split_bucket: True, # bool. whether to split the batch into multiple buckets.
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"return_fragment": False, # bool. step by step return the audio fragment.
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"speed_factor":1.0, # float. control the speed of the synthesized audio.
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"fragment_interval":0.3, # float. to control the interval of the audio fragment.
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"seed": -1, # int. random seed for reproducibility.
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"text": "", # str.(required) text to be synthesized
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"text_lang: "", # str.(required) language of the text to be synthesized
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"ref_audio_path": "", # str.(required) reference audio path
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"prompt_text": "", # str.(optional) prompt text for the reference audio
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"prompt_lang": "", # str.(required) language of the prompt text for the reference audio
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"top_k": 5, # int. top k sampling
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"top_p": 1, # float. top p sampling
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"temperature": 1, # float. temperature for sampling
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"text_split_method": "cut0", # str. text split method, see text_segmentaion_method.py for details.
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"batch_size": 1, # int. batch size for inference
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"batch_threshold": 0.75, # float. threshold for batch splitting.
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"split_bucket: True, # bool. whether to split the batch into multiple buckets.
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"return_fragment": False, # bool. step by step return the audio fragment.
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"speed_factor":1.0, # float. control the speed of the synthesized audio.
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"fragment_interval":0.3, # float. to control the interval of the audio fragment.
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"seed": -1, # int. random seed for reproducibility.
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}
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returns:
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tulpe[int, np.ndarray]: sampling rate and audio data.
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@ -606,7 +606,7 @@ class TTS:
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top_k:int = inputs.get("top_k", 5)
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top_p:float = inputs.get("top_p", 1)
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temperature:float = inputs.get("temperature", 1)
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text_split_method:str = inputs.get("text_split_method", "")
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text_split_method:str = inputs.get("text_split_method", "cut0")
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batch_size = inputs.get("batch_size", 1)
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batch_threshold = inputs.get("batch_threshold", 0.75)
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speed_factor = inputs.get("speed_factor", 1.0)
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@ -824,16 +824,13 @@ class TTS:
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if not return_fragment:
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print("%.3f\t%.3f\t%.3f\t%.3f" % (t1 - t0, t2 - t1, t_34, t_45))
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yield [
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self.audio_postprocess(audio,
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yield self.audio_postprocess(audio,
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self.configs.sampling_rate,
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batch_index_list,
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speed_factor,
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split_bucket,
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fragment_interval
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),
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f"<strong>text:</strong> {text} <strong>text_lang:</strong> {text_lang} <strong>prompt_text:</strong> {prompt_text} <strong>prompt_lang:</strong> {prompt_lang} <strong>top_k:</strong> {top_k} <strong>top_p:</strong> {top_p} <strong>temperature:</strong> {temperature} <strong>batch_size:</strong> {batch_size} <strong>batch_threshold:</strong> {batch_threshold} <strong>split_bucket:</strong> {split_bucket} <strong>return_fragment:</strong> {return_fragment} <strong>speed_factor:</strong> {speed_factor} <strong>fragment_interval:</strong> {fragment_interval} <strong>seed:</strong> {actual_seed}"
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]
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)
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except Exception as e:
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traceback.print_exc()
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@ -6,6 +6,7 @@
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全部按英文识别
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全部按日文识别
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'''
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import random
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import os, sys
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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@ -94,6 +95,7 @@ def inference(text, text_lang,
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split_bucket,fragment_interval,
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seed,
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):
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actual_seed = seed if seed not in [-1, "", None] else random.randrange(1 << 32)
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inputs={
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"text": text,
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"text_lang": dict_language[text_lang],
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@ -109,11 +111,10 @@ def inference(text, text_lang,
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"split_bucket":split_bucket,
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"return_fragment":False,
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"fragment_interval":fragment_interval,
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"seed":seed,
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"seed":actual_seed,
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}
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for item in tts_pipline.run(inputs):
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yield item
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yield item, actual_seed
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def custom_sort_key(s):
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# 使用正则表达式提取字符串中的数字部分和非数字部分
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@ -211,8 +212,6 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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with gr.Row():
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inference_button = gr.Button(i18n("合成语音"), variant="primary")
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stop_infer = gr.Button(i18n("终止合成"), variant="primary")
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with gr.Row():
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inference_details = gr.Markdown()
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inference_button.click(
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@ -226,7 +225,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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split_bucket,fragment_interval,
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seed
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],
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[output, inference_details],
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[output, seed],
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)
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stop_infer.click(tts_pipline.stop, [], [])
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