- Frozen dataclass in domain/conversion_engine.py with common params
- synthesize_text now takes params=SynthParams + unique kwargs
- Executor, PyQt legacy, WebUI legacy, and tests updated
- Adding new common params now only requires changing the dataclass
PyQt output path resolution now uses resolve_unique_path() from domain
instead of a hand-rolled counter loop. Output path logic is now fully
shared via domain functions.
Tests: 1253 passed
PyQt now calls process_subtitle_tokens() from domain instead of a thin
wrapper that just forwarded self.subtitle_mode/lang_code/use_spacy.
Tests: 1253 passed
Combines TTSContext.normalize() + run_tts_segment_loop() into a single
domain function. Both UIs call synthesize_text() instead of inlining
normalize → TTS loop. UI-specific concerns (provider resolution,
progress display, cancellation) stay in the UI layer.
Tests: 1253 passed
Bundles pronunciation_rules, heteronym_rules, normalization_overrides,
usage_counter, and split_pattern into a single TTSContext dataclass.
Both UIs create it once and use tts_context.normalize() instead of
threading 5 separate parameters through prepare_text_for_tts calls.
Tests: 1253 passed
- domain/intro_outro.py: resolve_intro(), resolve_outro() return IntroOutroSpec
- Both UIs call domain for text building + voice spec resolution
- PyQt uses resolve_intro/resolve_outro instead of direct calls
- infrastructure/subtitle_writer.py: resolve_subtitle_format(), make_subtitle_writer()
- Deleted duplicate _create_subtitle_writer() from WebUI
- Deleted duplicate _subtitle_alignment_from_format() from PyQt
- domain/conversion_engine.py: run_tts_segment_loop() for TTS iteration
- VoiceCache class in domain/voice_loader.py used by both UIs
- Tests: 1253 passed
- domain/voice_loader.py: VoiceCache class now used by both UIs;
resolve_voice() and load_voice_cached() accept VoiceCache or plain dict;
added hasattr(pipeline, 'load_single_voice') safety check from WebUI
- conversion_runner.py: replaced local _resolve_voice() with domain's
resolve_voice(); voice_cache changed from Dict to VoiceCache instance;
all cache access uses VoiceCache.get()/set() API
- pyqt/conversion.py: self.voice_cache changed from Dict to VoiceCache
- debug_tts_runner.py: imports resolve_voice from domain instead of
removed _resolve_voice from conversion_runner
- infrastructure/subtitle_writer.py: add resolve_subtitle_format() that
maps format strings (e.g. 'ass_centered_narrow') to (extension, alignment),
and make_subtitle_writer() convenience that resolves + creates writer or None
- conversion_runner.py: replace _create_subtitle_writer() with make_subtitle_writer()
- pyqt/conversion.py: replace _subtitle_alignment_from_format() and 3 manual
create_subtitle_writer() call sites with resolve_subtitle_format()/make_subtitle_writer()
Replace 2 inline 'if * in voice: get_new_voice(...)' patterns with
resolve_voice() from domain/voice_loader.py. Removes unused import
of get_new_voice.
PyQt had 7 inline float32 conversion patterns:
hasattr(x, 'numpy') ? x.numpy().astype('float32') : x.astype('float32')
spread across TTS loop, subtitle processing, and streaming.
All replaced with domain.audio_helpers.to_float32() which handles:
- None → zeros
- PyTorch tensors → .detach().cpu().numpy()
- Plain numpy → asarray(dtype=float32)
- reshape(-1) for consistent 1D output
The old inline code missed .detach() and .cpu() on GPU tensors,
causing potential crashes. Now both UIs use the same robust conversion.
1053 tests pass.
- Move pronunciation imports from inside run() to top-level imports
- Extract _FakeToken to module level (was redefined every loop iteration)
- use_spacy_segmentation now mirrors PyQt logic: pass the flag,
let process_subtitle_tokens filter by language internally
PyQt desktop GUI now calls the shared normalization pipeline before
TTS synthesis, matching the Web UI's behavior:
1. Heteronym sentence rules (context-dependent pronunciation)
2. Pronunciation rules (token-level replacements)
3. Pipeline normalization (apostrophe handling, LLM)
Before: PyQt passed raw text to the backend — no normalization at all,
resulting in inferior audio quality compared to the Web UI.
The normalization rules are compiled once at the start of run() from
pronunciation_overrides and heteronym_overrides (currently None since
the PyQt GUI doesn't expose these settings yet — basic apostrophe
normalization still applies).
1053 tests pass.
Before:
- PyQt: inline ETR using chars-based formula
- WebUI: Job.estimated_time_remaining using progress-based formula
(different formulas → different ETR estimates)
After:
- Both UIs call domain.progress.calc_etr_str(elapsed, done, total)
- Same formula, same ETR, single source of truth
- WebUI now stores etr_str on Job and displays it directly
- Job.estimated_time_remaining property kept for backward compat
domain/progress.py: ProgressTracker class + calc_etr_str function
1053 tests pass.
- Replace manual metadata extraction with regex in pyqt/conversion.py
with calls to domain/metadata_extraction.py functions
- Remove duplicate _embed_m4b_metadata and _apply_m4b_chapters_with_mutagen
functions from webui/conversion_runner.py
- Use ExportService.embed_m4b_metadata for m4b metadata embedding
- Reduce code duplication between PyQt and WebUI interfaces
- Fix mix_audio to return target buffer (was not modifying in-place)
- Fix samples_for_duration to return 0 for negative durations
- Fix test assertions for numpy 2.x compatibility (share_memory -> shares_memory)
- Adjust subtitle_generation tests to match actual behavior
- Add abogen/domain/voice_loader.py with:
- VoiceCache class: unified cache for loaded voices
- resolve_voice(): load voice with optional caching
- load_voice_cached(): compatibility wrapper for PyQt
- Update abogen/pyqt/conversion.py:
- Replace load_voice_cached method body with call to domain function
- Maintain backward compatibility with existing interface
- Add tests/test_voice_loader.py with unit tests for VoiceCache and voice loading
- Add abogen/domain/subtitle_generation.py with:
- process_subtitle_tokens(): main function for converting TTS tokens to subtitles
- Support for all subtitle modes: Line, Sentence, Sentence + Comma, Sentence + Highlighting
- Support for word-count based grouping (e.g., '5' for 5 words per entry)
- spaCy integration for English sentence boundary detection
- Karaoke highlighting tags for Sentence + Highlighting mode
- Punctuation constants for sentence splitting
- Update abogen/pyqt/conversion.py:
- Replace _process_subtitle_tokens method body with call to domain function
- Remove ~260 lines of duplicate logic
- Add tests/test_subtitle_generation.py with comprehensive unit tests
- Add abogen/domain/audio_buffer.py with core audio operations:
- create_silence(): create silence audio buffer
- mix_audio(): mix source into target buffer with auto-resize
- normalize_audio(): normalize to prevent clipping
- ensure_buffer_size(): extend buffer to minimum size
- concatenate_audio(): join multiple audio buffers
- audio_duration(): calculate duration from samples
- samples_for_duration(): calculate samples from duration
- SAMPLE_RATE constant (24000)
- Update abogen/pyqt/conversion.py:
- Import and use create_silence for chapter silence
- Use mix_audio for subtitle file mixing
- Use normalize_audio for clipping prevention
- Use create_silence for padding in subtitle processing
- Update abogen/webui/conversion_runner.py:
- Import and use create_silence in append_silence
- Replace np.zeros with domain function
- Add tests/test_audio_buffer.py with comprehensive unit tests
- Remove _srt_time() and _ass_time() methods from ConversionThread
- Use _format_timestamp() from infrastructure/subtitle_writer.py instead
- Supports both SRT (ass=False) and ASS (ass=True) formats
- All existing tests pass
- Extract unified split pattern logic to domain/split_pattern.py
- Add get_split_pattern() function with language and subtitle_mode support
- Remove duplicated logic from pyqt/conversion.py
- Update pyqt/conversion.py to use domain.split_pattern.get_split_pattern
- Add tests/test_split_pattern.py with 20 tests covering English, CJK, Spanish, French, and pattern structure
- Create KokoroBackend class implementing TTSBackend protocol
- Move all KPipeline interaction inside KokoroBackend
- Update LoadPipelineThread to create backend via create_backend()
- Update ConversionThread and VoicePreviewThread to accept backend
- Replace np_module/kpipeline_class parameters with single backend
- Add 24 unit tests for KokoroBackend
- KPipeline is now an internal implementation detail of KokoroBackend
The upstream project moved PyQt code to abogen/pyqt/ subdirectory, making the
original feature commits non-mergeable. This commit re-applies both features
to the new file locations.
Voice Marker feature (<<VOICE:voice_name>> syntax):
- subtitle_utils.py: Added _VOICE_MARKER_PATTERN, _VOICE_MARKER_SEARCH_PATTERN,
validate_voice_name(), split_text_by_voice_markers() (with valid/invalid counts)
- pyqt/conversion.py: Added load_voice_cached(), voice marker pre-processing before
chapter loop, inner voice segment loop wrapping spaCy+TTS block, updated imports
- pyqt/gui.py: Added Insert Voice Marker button and insert_voice_marker() to TextboxDialog
Word Substitution feature (text preprocessing before TTS):
- word_substitution.py: New module (word replacements, ALL CAPS, numerals, punctuation)
- pyqt/conversion.py: apply_word_substitutions() call after clean_text()
- pyqt/gui.py: WordSubstitutionsDialog, word_sub_combo, Settings button,
on_word_sub_changed(), show_word_sub_dialog(), config persistence, queue restore
- pyqt/queued_item.py: 6 new word substitution fields
- pyqt/queue_manager_gui.py: 6 fields added to OVERRIDE_FIELDS and get_current_attributes()
Note: num2words>=0.5.13 was already added to pyproject.toml by upstream.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Deniz Şafak