fix(segmentation): process TTS segments per sentence, fix all subtitle modes

Sentence modes processed all text as a whole: Pipeline.__call__ merged every
engine segment back into one (whole text, no per-token timings), producing a
single giant subtitle and whole-text progress logs.

- tts_plugin/types: add TokenTiming, AudioSegment, SynthesizedAudio.segments
- tts_plugin/utils: Pipeline yields one Segment per engine segment (with
  tokens); merged fallback only when engine provides none
- kokoro engine: expose per-segment graphemes/audio + per-word token timings
- supertonic engine: expose per-segment graphemes/audio (no tokens)
- split_pattern: English Sentence/Sentence+Comma engine split is newline-only
  (boundaries applied at subtitle time via spaCy); non-English Sentence+Comma
  with spaCy ON uses spaCy pre-segmentation + newline engine split (no
  commas); spaCy-off fallback keeps comma pattern
- tts_segments: restore inter-segment whitespace on real per-word token
  boundaries only (never FakeToken fallbacks)
- _to_language_enum: accept Language enum input (str(enum) is "Language.ES",
  silently resolved to EN_US and disabled spaCy pre-TTS for every language
  in WebUI)
- pyqt/conversion, utils: replace print with logging
- add AGENTS.md documenting the segmentation/subtitle contract for future
  sessions
- tests: update English split-pattern expectations (1566 passing)

AGENTS.md

@@ -0,0 +1,82 @@
+# AGENTS.md — Segmentation & Subtitle System Contract
+
+This document is the source of truth for how text is split for **voice
+processing** (TTS engine segmentation) and **subtitle processing**, across
+languages, TTS engines, and subtitle modes. It was written after a bug where
+sentence modes "processed all text as a whole" (one merged engine segment →
+one giant subtitle). **Do not change this behavior without updating this
+table.**
+
+## Voice processing — split pattern passed to the TTS engine
+
+`get_split_pattern(language, mode)` in `abogen/domain/split_pattern.py` is the
+default; the spaCy pre-TTS path overrides it. Both UIs must stay in sync:
+`spacy_pre_tts_segmentation` (`abogen/domain/conversion_pipeline.py`, WebUI)
+and the inline branch in `abogen/pyqt/conversion.py` (~line 860, PyQt).
+
+| Subtitle mode | English (en-US/en-GB) | Non-English, spaCy ON | Non-English, spaCy OFF | CJK (ja/zh) |
+|---|---|---|---|---|
+| Disabled | `\n` | spaCy pre-split, engine `\n` | `\n+` | `(?<=[.!?؟。！？।])\s*\|\n+` |
+| Line | `\n` | spaCy pre-split, engine `\n` | `\n` | `(?<=[.!?؟。！？।])\s*\|\n+` |
+| Sentence | `\n` | spaCy pre-split, engine `\n` | `(?<=[.!?؟。！？।])\s+\|\n+` | `(?<=[.!?؟。！？।])\s*\|\n+` |
+| Sentence + Comma | `\n` | spaCy pre-split, engine `\n` | `(?<=[.!?,؟。！？،،、।])\s+\|\n+` (commas kept) | `(?<=[.!?,؟。！？،،、।])\s*\|\n+` |
+| Sentence + Highlighting | `\n+` | `\n+` | `\n+` | `\n+` |
+| N words ("5 words") | `\n` (→ Disabled) | `\n+` | `\n+` | Disabled CJK pattern |
+
+Rules baked into this table:
+
+- **English voice splitting is ALWAYS newline-only** for Disabled, Line,
+  Sentence, and Sentence + Comma. English sentence/comma boundaries are
+  produced ONLY at subtitle time (spaCy post-TTS / regex fallback). Never add
+  punctuation to the English engine pattern.
+- **Non-English + spaCy ON**: spaCy pre-segments the text (pre-TTS); the
+  engine pattern is `\n` for Sentence AND Sentence + Comma — **never commas**.
+  spaCy is skipped when the toggle is off, mode is Disabled/Line, or input is
+  a subtitle file.
+- **Non-English + spaCy OFF** (toggle off, spaCy failure, subtitle input): the
+  default pattern is used — Sentence + Comma KEEPS its commas here. This is
+  the intentional fallback, not a bug.
+- CJK: punctuation-based patterns for Disabled/Line (historical); spacing is
+  `\s*` (no spaces needed between CJK chars).
+- Engine-level extra chunking (applies after the pattern): kokoro English
+  re-chunks at ~510 phonemes; kokoro non-English at ~400 chars; supertonic
+  caps each part at 300 chars.
+
+## Subtitle processing — post-TTS, from tokens
+
+| Mode | Behavior |
+|---|---|
+| Disabled | no subtitles |
+| Line | one entry per TTS segment (line) |
+| Sentence | sentence boundaries: English → spaCy; others → regex on `[.!?…]` |
+| Sentence + Comma | sentence + comma boundaries at subtitle time (both languages) — commas never affect voice |
+| Sentence + Highlighting | karaoke `{\kf…}` per word, grouped by sentence |
+| N words | groups of N words by whitespace counting |
+
+Token granularity (timing quality): kokoro English emits **per-word tokens**
+with timestamps; kokoro non-English and supertonic emit **no tokens** → each
+engine segment becomes one FakeToken, split by regex with proportional timing
+when it contains multiple sentences.
+
+## Hard invariants (breaking these reintroduces the original bug)
+
+1. `Pipeline.__call__` (`abogen/tts_plugin/utils.py`) must yield ONE `Segment`
+   per engine segment (with tokens) — never merge segments back into the
+   whole text. `SynthesizedAudio.segments` carries the per-segment data;
+   engines expose it in `plugins/kokoro/engine.py` and
+   `plugins/supertonic/engine.py`.
+2. `tts_segments` (`abogen/domain/conversion_pipeline.py`) restores trailing
+   whitespace on segment-boundary tokens ONLY for real per-word tokens, never
+   for FakeToken fallbacks.
+3. `_to_language_enum` must return `lang_code` as-is when it is already a
+   `Language` enum (`str(Language.ES)` is `"Language.ES"`, which silently
+   resolved to EN_US and disabled spaCy pre-TTS for every language in WebUI).
+4. English must never use spaCy for PRE-TTS segmentation — only for subtitles.
+
+## Guarded by tests
+
+- `tests/test_split_pattern.py` — English newline-only; non-English sentence
+  patterns; CJK behavior.
+- `tests/test_domain_conversion_pipeline.py` — `tts_segments` / spaCy
+  segmentation helpers.
+- Full suite: `python -m pytest tests/ -q` (expect 1566+ passing).

abogen/domain/conversion_pipeline.py

@@ -60,7 +60,7 @@ def spacy_pre_tts_segmentation(
         text_segments is a list of sentences (always at least one element).
         active_split_pattern is the regex to use for TTS backend splitting.
     """
-    from abogen.domain.split_pattern import PUNCTUATION_COMMAS, get_split_pattern
+    from abogen.domain.split_pattern import get_split_pattern
 
     def _log(msg: str) -> None:
         if log_callback:
@@ -99,13 +99,10 @@ def spacy_pre_tts_segmentation(
 
     _log(f"spaCy: Text segmented into {len(spacy_sentences)} sentences...")
 
-    # Compute split_pattern override based on subtitle mode
+    # spaCy already split at sentence boundaries; the engine only needs to
-    spacing_pattern = r"\s*" if lang_enum in _CJK_LANGS else r"\s+"
+    # split on newlines. Commas are never used in the engine split pattern
-
+    # for non-English (Sentence + Comma splits at commas only at subtitle
-    if subtitle_mode_str == "Sentence + Comma":
+    # time, like English).
-        active_split = r"(?<=[{}]){}|\n+".format(PUNCTUATION_COMMAS, spacing_pattern)
-    else:
-        # Sentence mode: spaCy already split, only split on newlines
     active_split = "\n"
 
     return spacy_sentences, active_split
@@ -113,6 +110,8 @@ def spacy_pre_tts_segmentation(
 
 def _to_language_enum(lang_code: Any) -> Language:
     """Convert lang_code to Language enum (ISO code or Language enum)."""
+    if isinstance(lang_code, Language):
+        return lang_code
     try:
         return Language.from_str(str(lang_code))
     except ValueError:
@@ -174,6 +173,8 @@ def tts_segments(
     segment_iter = backend(text, **kwargs)
 
     chunk_start = current_time
+    prev_tokens: Optional[List[Dict[str, Any]]] = None
+    prev_was_fallback = True
 
     for segment in segment_iter:
         graphemes_raw = getattr(segment, "graphemes", "") or ""
@@ -186,8 +187,10 @@ def tts_segments(
         duration = len(audio) / SAMPLE_RATE
 
         tokens_list = getattr(segment, "tokens", [])
+        was_fallback = False
         if not tokens_list and graphemes:
             tokens_list = [FakeToken(graphemes, 0, duration)]
+            was_fallback = True
 
         tokens = [
             {
@@ -199,6 +202,18 @@ def tts_segments(
             for tok in tokens_list
         ]
 
+        # When the engine splits text on a punctuation pattern, the
+        # whitespace between segments is consumed by the split. Restore a
+        # trailing space on the boundary token of the previous segment so
+        # subtitle processing sees the original spacing (only for real
+        # per-word tokens; FakeToken fallbacks split via their own logic).
+        if (
+            not prev_was_fallback
+            and prev_tokens
+            and not prev_tokens[-1].get("whitespace")
+        ):
+            prev_tokens[-1]["whitespace"] = " "
+
         yield SegmentResult(
             graphemes=graphemes,
             audio=audio,
@@ -207,6 +222,8 @@ def tts_segments(
             tokens=tokens,
         )
 
+        prev_tokens = tokens
+        prev_was_fallback = was_fallback
         chunk_start += duration
 
 

abogen/domain/split_pattern.py

@@ -27,8 +27,17 @@ def get_split_pattern(language: Language, subtitle_mode: str) -> str:
     except ValueError:
         mode = SubtitleMode.DISABLED
 
-    # For English, always use newline splitting only
+    # English: spaCy is NOT used for pre-TTS segmentation (it is only used
+    # for post-TTS subtitle boundaries), so sentence boundaries for English
+    # are applied at subtitle time, not in the TTS engine. Disabled, Line,
+    # Sentence, and Sentence + Comma all keep newline-only engine splitting.
     if language in (Language.EN_US, Language.EN_GB):
+        if mode in (
+            SubtitleMode.DISABLED,
+            SubtitleMode.LINE,
+            SubtitleMode.SENTENCE,
+            SubtitleMode.SENTENCE_COMMA,
+        ):
             return "\n"
 
     # Determine spacing pattern based on language

abogen/pyqt/conversion.py

@@ -1,5 +1,6 @@
 import os
 import time
+import logging
 import hashlib  # For generating unique cache filenames
 from pathlib import Path
 from platformdirs import user_desktop_dir
@@ -50,6 +51,8 @@ import abogen.hf_tracker as hf_tracker
 import static_ffmpeg
 import threading  # for efficient waiting
 
+logger = logging.getLogger(__name__)
+
 
 
 # Configuration constants
@@ -64,7 +67,6 @@ from abogen.subtitle_utils import (
     sanitize_name_for_os,
     split_text_by_voice_markers
 )
-from abogen.domain.split_pattern import PUNCTUATION_COMMAS
 
 class CountdownDialog(QDialog):
     """Base dialog with auto-accept countdown functionality"""
@@ -348,7 +350,7 @@ class ConversionThread(QThread):
         return samples_processed
 
     def run(self):
-        print(
+        logger.info(
             f"\nVoice: {self.voice}\nLanguage: {self.lang_code}\nSpeed: {self.speed}\nGPU: {self.use_gpu}\nFile: {self.file_name}\nSubtitle mode: {self.subtitle_mode}\nOutput format: {self.output_format}\nSave option: {self.save_option}\n"
         )
         try:
@@ -873,7 +875,6 @@ class ConversionThread(QThread):
                     )
                     spacy_sentences = None
                     active_split_pattern = self.split_pattern
-                    spacing_pattern = r"\s*" if self.lang_code in (Language.JA, Language.ZH) else r"\s+"
 
                     # Pre-load spaCy model for English if it will be needed for subtitle generation
                     if (
@@ -914,15 +915,11 @@ class ConversionThread(QThread):
                                     "grey",
                                 )
                             )
-                            # For Sentence + Comma mode, still split on commas within spaCy sentences
+                            # spaCy already split at sentence boundaries; the
-                            if self.subtitle_mode == "Sentence + Comma":
+                            # engine only splits on newlines. Commas are never
-                                active_split_pattern = r"(?<=[{}]){}|\n+".format(
+                            # used in the engine split pattern (Sentence +
-                                    PUNCTUATION_COMMAS, spacing_pattern
+                            # Comma splits at commas only at subtitle time).
-                                )
+                            active_split_pattern = "\n"
-                            else:
-                                active_split_pattern = (
-                                    "\n"  # Use newline splitting for Sentence mode
-                                )
                         else:
                             self.log_updated.emit(
                                 ("\nspaCy: Fallback to default segmentation...", "grey")
@@ -933,10 +930,10 @@ class ConversionThread(QThread):
 
                     # Print active split pattern used by the TTS engine once for this batch
                     try:
-                        print(f"Using split pattern: {active_split_pattern!r}")
+                        logger.info(f"Using split pattern: {active_split_pattern!r}")
                     except Exception:
-                        # Print must never break processing
+                        # Logging must never break processing
-                        print("Using split pattern: (unprintable)")
+                        logger.warning("Using split pattern: (unprintable)")
 
                     for text_segment in text_segments:
                         def _qt_check_cancel() -> bool:
@@ -1445,7 +1442,7 @@ class VoicePreviewThread(QThread):
         return os.path.join(self.cache_dir, filename)
 
     def run(self):
-        print(
+        logger.info(
             f"\nVoice: {self.voice}\nLanguage: {self.lang_code}\nSpeed: {self.speed}\nGPU: {self.use_gpu}\n"
         )
 

abogen/tts_plugin/types.py

@@ -79,6 +79,44 @@ class SynthesisRequest:
     format: AudioFormat
 
 
+@dataclass(frozen=True)
+class TokenTiming:
+    """Per-token timing within a synthesized segment.
+
+    Attributes:
+        text: Token text.
+        whitespace: Whitespace following the token ("" if none).
+        start: Start time in seconds (relative to segment start).
+        end: End time in seconds (relative to segment start).
+    """
+
+    text: str
+    whitespace: str = ""
+    start: float = 0.0
+    end: float = 0.0
+
+
+@dataclass(frozen=True)
+class AudioSegment:
+    """One contiguous synthesized segment (sentence-level chunk).
+
+    Engines that split the input text (via ``split_pattern``) expose each
+    chunk as its own AudioSegment so hosts can report per-sentence progress
+    and build subtitles from per-token timings.
+
+    Attributes:
+        graphemes: The text this segment was synthesized from.
+        audio: Raw float32 PCM audio bytes for this segment.
+        sample_rate: Sample rate of ``audio``.
+        tokens: Per-token timing details, when the engine provides them.
+    """
+
+    graphemes: str
+    audio: bytes
+    sample_rate: int
+    tokens: tuple[TokenTiming, ...] = ()
+
+
 @dataclass(frozen=True)
 class SynthesizedAudio:
     """Immutable value object for synthesized audio result.
@@ -87,11 +125,15 @@ class SynthesizedAudio:
         data: Raw audio bytes.
         format: Audio format of the result.
         duration: Duration of the audio.
+        segments: Per-segment details when the engine split the text into
+            sentence-level chunks (empty for engines that only produce a
+            single merged result).
     """
 
     data: bytes
     format: AudioFormat
     duration: Duration
+    segments: tuple[AudioSegment, ...] = ()
 
 
 @dataclass(frozen=True)

abogen/tts_plugin/utils.py

@@ -169,15 +169,38 @@ class Pipeline:
         )
 
         result = session.synthesize(request)
-        audio_array = np.frombuffer(result.data, dtype=np.float32)
 
-        from dataclasses import dataclass
+        from dataclasses import dataclass, field
+
+        @dataclass
+        class Token:
+            text: str
+            whitespace: str = ""
+            start_ts: float = 0.0
+            end_ts: float = 0.0
 
         @dataclass
         class Segment:
             graphemes: str
             audio: np.ndarray
+            tokens: list[Any] = field(default_factory=list)
 
+        if result.segments:
+            for seg in result.segments:
+                audio_array = np.frombuffer(seg.audio, dtype=np.float32)
+                tokens = [
+                    Token(
+                        text=tok.text,
+                        whitespace=tok.whitespace,
+                        start_ts=tok.start,
+                        end_ts=tok.end,
+                    )
+                    for tok in seg.tokens
+                ]
+                yield Segment(graphemes=seg.graphemes, audio=audio_array, tokens=tokens)
+            return
+
+        audio_array = np.frombuffer(result.data, dtype=np.float32)
         yield Segment(graphemes=text, audio=audio_array)
 
     def load_single_voice(self, voice_name: str) -> Any:

abogen/utils.py

@@ -16,6 +16,8 @@ from functools import lru_cache
 
 from dotenv import load_dotenv, find_dotenv
 
+logger = logging.getLogger(__name__)
+
 
 def _load_environment() -> None:
     explicit_path = os.environ.get("ABOGEN_ENV_FILE")
@@ -441,10 +443,6 @@ default_encoding = sys.getfilesystemencoding()
 
 
 def create_process(cmd, stdin=None, text=True, capture_output=False):
-    import logging
-
-    logger = logging.getLogger(__name__)
-
     # Configure root logger to output to console if not already configured
     root = logging.getLogger()
     if not root.handlers:
@@ -493,8 +491,8 @@ def create_process(cmd, stdin=None, text=True, capture_output=False):
             }
         )
 
-    # Print the command being executed
+    # Log the command being executed
-    print(f"Executing: {cmd if isinstance(cmd, str) else ' '.join(cmd)}")
+    logger.info(f"Executing: {cmd if isinstance(cmd, str) else ' '.join(cmd)}")
 
     proc = subprocess.Popen(cmd, **kwargs)
 
@@ -615,7 +613,7 @@ def prevent_sleep_start():
             )
         else:
             # Non-systemd distro or systemd tools not installed: skip inhibition rather than crash
-            print(
+            logger.warning(
                 "systemd-inhibit not found: skipping sleep inhibition on this Linux system."
             )
 

plugins/kokoro/engine.py

@@ -22,9 +22,11 @@ from abogen.tts_plugin.errors import EngineError
 from abogen.tts_plugin.manifest import VoiceManifest
 from abogen.tts_plugin.types import (
     AudioFormat,
+    AudioSegment,
     Duration,
     SynthesisRequest,
     SynthesizedAudio,
+    TokenTiming,
 )
 
 logger = logging.getLogger(__name__)
@@ -117,7 +119,9 @@ class KokoroSession:
             speed = request.parameters.values.get("speed", 1.0)
             split_pattern = request.parameters.values.get("split_pattern", None)
 
+            sample_rate = _KOKORO_SAMPLE_RATE
             audio_parts: list[np.ndarray] = []
+            segments: list[AudioSegment] = []
             for segment in self._pipeline(
                 request.text,
                 voice=voice,
@@ -127,7 +131,28 @@ class KokoroSession:
                 audio = segment.audio
                 if hasattr(audio, "numpy"):
                     audio = audio.numpy()
-                audio_parts.append(np.asarray(audio, dtype="float32"))
+                audio = np.asarray(audio, dtype="float32")
+                if audio.size == 0:
+                    continue
+                audio_parts.append(audio)
+
+                tokens = tuple(
+                    TokenTiming(
+                        text=str(tok.text),
+                        whitespace=str(tok.whitespace or ""),
+                        start=float(tok.start_ts or 0.0),
+                        end=float(tok.end_ts or 0.0),
+                    )
+                    for tok in (getattr(segment, "tokens", None) or [])
+                )
+                segments.append(
+                    AudioSegment(
+                        graphemes=str(getattr(segment, "graphemes", "") or ""),
+                        audio=audio.tobytes(),
+                        sample_rate=sample_rate,
+                        tokens=tokens,
+                    )
+                )
 
             if not audio_parts:
                 return SynthesizedAudio(
@@ -138,12 +163,13 @@ class KokoroSession:
 
             combined = np.concatenate(audio_parts).astype("float32", copy=False)
             audio_bytes = combined.tobytes()
-            duration_seconds = len(combined) / _KOKORO_SAMPLE_RATE
+            duration_seconds = len(combined) / sample_rate
 
             return SynthesizedAudio(
                 data=audio_bytes,
                 format=AudioFormat(mime="audio/wav", extension="wav"),
                 duration=Duration(seconds=duration_seconds),
+                segments=tuple(segments),
             )
         except EngineError:
             raise

plugins/supertonic/engine.py

@@ -19,6 +19,7 @@ from abogen.tts_plugin.errors import EngineError
 from abogen.tts_plugin.manifest import VoiceManifest
 from abogen.tts_plugin.types import (
     AudioFormat,
+    AudioSegment,
     Duration,
     SynthesisRequest,
     SynthesizedAudio,
@@ -113,6 +114,7 @@ class SuperTonicSession:
                 total_steps = int(total_steps)
 
             audio_parts: list[np.ndarray] = []
+            segments: list[AudioSegment] = []
             for segment in self._pipeline(
                 request.text,
                 voice=voice,
@@ -120,7 +122,17 @@ class SuperTonicSession:
                 split_pattern=split_pattern,
                 total_steps=total_steps,
             ):
-                audio_parts.append(segment.audio)
+                audio = np.asarray(segment.audio, dtype="float32")
+                if audio.size == 0:
+                    continue
+                audio_parts.append(audio)
+                segments.append(
+                    AudioSegment(
+                        graphemes=str(getattr(segment, "graphemes", "") or ""),
+                        audio=audio.tobytes(),
+                        sample_rate=self._pipeline.sample_rate,
+                    )
+                )
 
             if not audio_parts:
                 return SynthesizedAudio(
@@ -139,6 +151,7 @@ class SuperTonicSession:
                 data=audio_bytes,
                 format=AudioFormat(mime="audio/wav", extension="wav"),
                 duration=Duration(seconds=duration_seconds),
+                segments=tuple(segments),
             )
         except EngineError:
             raise

tests/test_split_pattern.py

@@ -9,7 +9,7 @@ from abogen.domain.enums import Language
 from abogen.domain.split_pattern import get_split_pattern
 
 
-# --- English always returns \n ---
+# --- English: newline-only for Disabled/Line, punctuation-based for sentence modes ---
 
 class TestEnglish:
     def test_english_sentence(self):