mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2026-05-12 12:58:10 +08:00
17cb2e5acf
Add support for G2PW processing in the TTS system by introducing new methods and classes for handling G2PW segments. Update PrepareCoordinator to manage G2PW worker threads and integrate G2PW profiling into the existing framework. Enhance text preprocessing to identify segments requiring G2PW and streamline the resolution of these segments. This update improves the overall performance and maintainability of the TTS system by optimizing the handling of Chinese text processing.
113 lines
3.9 KiB
Python
113 lines
3.9 KiB
Python
import os
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import re
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import sys
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from typing import Dict, List, Optional, Tuple
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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from text.LangSegmenter import LangSegmenter
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from text import cleaned_text_to_sequence
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from text import chinese2
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from text.cleaner import clean_text
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PreparedTextSegmentPayload = Dict[str, object]
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def split_text_by_language(text: str, language: str) -> Tuple[List[str], List[str]]:
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textlist: List[str] = []
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langlist: List[str] = []
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if language == "all_zh":
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for tmp in LangSegmenter.getTexts(text, "zh"):
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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elif language == "all_yue":
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for tmp in LangSegmenter.getTexts(text, "zh"):
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if tmp["lang"] == "zh":
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tmp["lang"] = "yue"
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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elif language == "all_ja":
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for tmp in LangSegmenter.getTexts(text, "ja"):
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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elif language == "all_ko":
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for tmp in LangSegmenter.getTexts(text, "ko"):
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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elif language == "en":
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langlist.append("en")
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textlist.append(text)
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elif language == "auto":
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for tmp in LangSegmenter.getTexts(text):
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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elif language == "auto_yue":
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for tmp in LangSegmenter.getTexts(text):
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if tmp["lang"] == "zh":
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tmp["lang"] = "yue"
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langlist.append(tmp["lang"])
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textlist.append(tmp["text"])
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else:
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for tmp in LangSegmenter.getTexts(text):
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if langlist:
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same_group = (tmp["lang"] == "en" and langlist[-1] == "en") or (
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tmp["lang"] != "en" and langlist[-1] != "en"
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)
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if same_group:
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textlist[-1] += tmp["text"]
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continue
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if tmp["lang"] == "en":
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langlist.append(tmp["lang"])
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else:
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langlist.append(language)
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textlist.append(tmp["text"])
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return textlist, langlist
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def clean_text_segment(text: str, language: str, version: str) -> Tuple[List[int], Optional[List[int]], str]:
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normalized_language = language.replace("all_", "")
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phones, word2ph, norm_text = clean_text(text, normalized_language, version)
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phones = cleaned_text_to_sequence(phones, version)
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return list(phones), None if word2ph is None else list(word2ph), str(norm_text)
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def preprocess_text_segments_payload(
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text: str,
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language: str,
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version: str,
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final: bool = False,
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) -> List[PreparedTextSegmentPayload]:
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text = re.sub(r" {2,}", " ", text)
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textlist, langlist = split_text_by_language(text, language)
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payloads: List[PreparedTextSegmentPayload] = []
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total_phones_len = 0
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for segment_text, segment_lang in zip(textlist, langlist):
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normalized_language = segment_lang.replace("all_", "")
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if normalized_language == "zh":
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norm_text = chinese2.text_normalize(segment_text)
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phones = []
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word2ph = None
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needs_g2pw = True
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estimated_phones_len = max(0, len(norm_text) * 2)
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else:
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phones, word2ph, norm_text = clean_text_segment(segment_text, segment_lang, version)
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needs_g2pw = False
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estimated_phones_len = len(phones)
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payloads.append(
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{
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"language": normalized_language,
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"phones": phones,
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"word2ph": word2ph,
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"norm_text": norm_text,
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"needs_g2pw": needs_g2pw,
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}
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)
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total_phones_len += int(estimated_phones_len)
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if not final and total_phones_len < 6:
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return preprocess_text_segments_payload("." + text, language, version, final=True)
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return payloads
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