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https://github.com/denizsafak/abogen.git
synced 2026-09-20 11:40:57 +02:00
refactor: move voice marker functions to domain/voice_markers.py
This commit is contained in:
Artem Akymenko
@@ -25,7 +25,7 @@ from abogen.domain.file_type import auto_select_relevant_chapters
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from abogen.domain.intro_outro import resolve_intro, resolve_outro
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from abogen.domain.metadata_extraction import extract_metadata_for_file
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from abogen.domain.metadata_merge import merge_metadata
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from abogen.subtitle_utils import split_text_by_voice_markers
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from abogen.domain.voice_markers import split_text_by_voice_markers
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def build_conversion_plan(request: ConversionRequest) -> ConversionPlan:
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@@ -274,7 +274,7 @@ def _build_segments(
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# Check for voice markers (PyQt style)
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# Detect markers even if validation fails (voice names may not be loaded yet)
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from abogen.subtitle_utils import _VOICE_MARKER_SEARCH_PATTERN
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from abogen.domain.voice_markers import _VOICE_MARKER_SEARCH_PATTERN
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has_voice_markers = bool(_VOICE_MARKER_SEARCH_PATTERN.search(body_text))
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voice_segments, last_voice, valid_count, invalid_count = split_text_by_voice_markers(
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@@ -0,0 +1,117 @@
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"""Voice marker parsing and text splitting.
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Handles <<VOICE:name>> markers in text, splitting text into voice-specific
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segments. This is domain logic about text segmentation by voice, not subtitle
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processing.
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"""
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from __future__ import annotations
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import re
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from typing import List, Tuple
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_VOICE_MARKER_PATTERN = re.compile(r"<<VOICE:[^>]*>>")
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_VOICE_MARKER_SEARCH_PATTERN = re.compile(r"<<VOICE:(.*?)>>")
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def validate_voice_name(voice_name: str) -> Tuple[bool, str | None]:
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"""Validate voice name against available voices (case-insensitive).
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Handles both single voices and formulas like 'af_heart*0.5 + am_echo*0.5'.
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Returns:
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Tuple of (is_valid, invalid_voice_name):
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- is_valid: True if all voices in the name/formula are valid
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- invalid_voice_name: The first invalid voice found, or None if all valid
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"""
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from abogen.tts_plugin.utils import get_voices
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voice_lookup_lower = {v.lower() for v in get_voices("kokoro")}
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voice_name = voice_name.strip()
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if "*" in voice_name:
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voices = voice_name.split("+")
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for term in voices:
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if "*" in term:
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base_voice = term.split("*")[0].strip()
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if base_voice.lower() not in voice_lookup_lower:
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return False, base_voice
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return True, None
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else:
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if voice_name.lower() not in voice_lookup_lower:
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return False, voice_name
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return True, None
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def split_text_by_voice_markers(
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text: str, default_voice: str
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) -> Tuple[List[Tuple[str, str]], str, int, int]:
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"""Split text by voice markers, returning list of (voice, text) tuples.
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Returns the last voice used so it can persist across chapters.
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Voice names are normalized to lowercase to match canonical voice names.
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Args:
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text: Text potentially containing <<VOICE:name>> markers
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default_voice: Voice to use if no markers found or before first marker
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Returns:
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Tuple of (segments_list, last_voice_used, valid_count, invalid_count):
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- segments_list: List of (voice_name, segment_text) tuples
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- last_voice_used: The voice that should continue into next chapter
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- valid_count: Number of valid voice markers processed
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- invalid_count: Number of invalid voice markers skipped
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"""
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from abogen.tts_plugin.utils import get_voices
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voice_splits = list(_VOICE_MARKER_SEARCH_PATTERN.finditer(text))
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if not voice_splits:
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return [(default_voice, text)], default_voice, 0, 0
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segments: List[Tuple[str, str]] = []
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current_voice = default_voice
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valid_markers = 0
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invalid_markers = 0
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first_start = voice_splits[0].start()
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if first_start > 0:
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intro_text = text[:first_start].strip()
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if intro_text:
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segments.append((current_voice, intro_text))
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for idx, match in enumerate(voice_splits):
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voice_name = match.group(1).strip()
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start = match.end()
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end = voice_splits[idx + 1].start() if idx + 1 < len(voice_splits) else len(text)
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segment_text = text[start:end].strip()
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is_valid, invalid_voice = validate_voice_name(voice_name)
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if is_valid:
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if "*" in voice_name:
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normalized_parts = []
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for part in voice_name.split("+"):
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part = part.strip()
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if "*" in part:
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voice_part, weight = part.split("*", 1)
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voice_part_lower = voice_part.strip().lower()
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canonical_voice = next(
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(v for v in get_voices("kokoro") if v.lower() == voice_part_lower),
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voice_part.strip()
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)
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normalized_parts.append(f"{canonical_voice}*{weight.strip()}")
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current_voice = " + ".join(normalized_parts)
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else:
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voice_name_lower = voice_name.lower()
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current_voice = next(
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(v for v in get_voices("kokoro") if v.lower() == voice_name_lower),
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voice_name
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)
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valid_markers += 1
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else:
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invalid_markers += 1
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if segment_text:
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segments.append((current_voice, segment_text))
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return segments, current_voice, valid_markers, invalid_markers
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+6
-116
@@ -465,120 +465,10 @@ def sanitize_name_for_os(name, is_folder=True):
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return sanitized
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def validate_voice_name(voice_name):
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"""Validate voice name against available voices (case-insensitive).
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Handles both single voices and formulas like 'af_heart*0.5 + am_echo*0.5'.
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Args:
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voice_name: Voice name or formula string to validate
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Returns:
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Tuple of (is_valid, invalid_voice_name):
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- is_valid: True if all voices in the name/formula are valid
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- invalid_voice_name: The first invalid voice found, or None if all valid
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"""
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from abogen.tts_plugin.utils import get_voices
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# Create case-insensitive lookup set (done once per call)
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voice_lookup_lower = {v.lower() for v in get_voices("kokoro")}
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voice_name = voice_name.strip()
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# Check if it's a formula (contains *)
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if "*" in voice_name:
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# Extract voice names from formula
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voices = voice_name.split("+")
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for term in voices:
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if "*" in term:
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base_voice = term.split("*")[0].strip()
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# Case-insensitive comparison
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if base_voice.lower() not in voice_lookup_lower:
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return False, base_voice
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return True, None
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else:
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# Single voice - case-insensitive comparison
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if voice_name.lower() not in voice_lookup_lower:
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return False, voice_name
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return True, None
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def split_text_by_voice_markers(text, default_voice):
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"""Split text by voice markers, returning list of (voice, text) tuples.
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IMPORTANT: Returns the last voice used so it can persist across chapters.
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Voice names are normalized to lowercase to match canonical voice names.
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Args:
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text: Text potentially containing <<VOICE:name>> markers
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default_voice: Voice to use if no markers found or before first marker
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Returns:
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Tuple of (segments_list, last_voice_used, valid_count, invalid_count):
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- segments_list: List of (voice_name, segment_text) tuples
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- last_voice_used: The voice that should continue into next chapter
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- valid_count: Number of valid voice markers processed
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- invalid_count: Number of invalid voice markers skipped
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"""
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from abogen.tts_plugin.utils import get_voices
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voice_splits = list(_VOICE_MARKER_SEARCH_PATTERN.finditer(text))
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if not voice_splits:
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# No voice markers, return entire text with default voice
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return [(default_voice, text)], default_voice, 0, 0
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segments = []
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current_voice = default_voice
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valid_markers = 0
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invalid_markers = 0
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# Text before first marker uses default voice
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first_start = voice_splits[0].start()
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if first_start > 0:
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intro_text = text[:first_start].strip()
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if intro_text:
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segments.append((current_voice, intro_text))
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# Process each voice marker
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for idx, match in enumerate(voice_splits):
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voice_name = match.group(1).strip()
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start = match.end()
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end = voice_splits[idx + 1].start() if idx + 1 < len(voice_splits) else len(text)
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segment_text = text[start:end].strip()
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# Validate voice name
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is_valid, invalid_voice = validate_voice_name(voice_name)
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if is_valid:
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# Normalize to lowercase to match canonical form
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# Handle both single voices and formulas
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if "*" in voice_name:
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# Normalize each voice in the formula
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normalized_parts = []
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for part in voice_name.split("+"):
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part = part.strip()
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if "*" in part:
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voice_part, weight = part.split("*", 1)
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# Find the canonical (lowercase) voice name
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voice_part_lower = voice_part.strip().lower()
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canonical_voice = next(
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(v for v in get_voices("kokoro") if v.lower() == voice_part_lower),
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voice_part.strip()
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# Backward-compatible re-exports — canonical location is domain/voice_markers.py
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from abogen.domain.voice_markers import ( # noqa: E402, F401
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validate_voice_name,
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split_text_by_voice_markers,
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_VOICE_MARKER_PATTERN,
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_VOICE_MARKER_SEARCH_PATTERN,
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)
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normalized_parts.append(f"{canonical_voice}*{weight.strip()}")
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current_voice = " + ".join(normalized_parts)
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else:
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# Find the canonical (lowercase) voice name
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voice_name_lower = voice_name.lower()
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current_voice = next(
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(v for v in get_voices("kokoro") if v.lower() == voice_name_lower),
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voice_name
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)
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valid_markers += 1
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else:
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# Invalid voice - stay with previous voice
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invalid_markers += 1
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if segment_text:
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segments.append((current_voice, segment_text))
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# Return segments, last voice, and counts
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return segments, current_voice, valid_markers, invalid_markers
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