feat: Integrate Supertonic TTS provider with configuration options and UI updates; enhance voice handling and settings management

abogen/tts_supertonic.py

@@ -0,0 +1,146 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+import math
+import re
+from typing import Any, Iterable, Iterator, Optional
+
+import numpy as np
+
+
+DEFAULT_SUPERTONIC_VOICES = ("M1", "M2", "M3", "M4", "M5", "F1", "F2", "F3", "F4", "F5")
+
+
+@dataclass
+class SupertonicSegment:
+    graphemes: str
+    audio: np.ndarray
+
+
+def _ensure_float32_mono(wav: Any) -> np.ndarray:
+    arr = np.asarray(wav, dtype="float32")
+    if arr.ndim == 2:
+        # (n, 1) or (1, n) or (n, channels)
+        if arr.shape[0] == 1 and arr.shape[1] > 1:
+            arr = arr.reshape(-1)
+        else:
+            arr = arr[:, 0]
+    return arr.reshape(-1)
+
+
+def _resample_linear(audio: np.ndarray, src_rate: int, dst_rate: int) -> np.ndarray:
+    if src_rate == dst_rate:
+        return audio
+    if audio.size == 0:
+        return audio
+    ratio = dst_rate / float(src_rate)
+    new_len = int(round(audio.size * ratio))
+    if new_len <= 1:
+        return np.zeros(0, dtype="float32")
+    x_old = np.linspace(0.0, 1.0, num=audio.size, endpoint=False)
+    x_new = np.linspace(0.0, 1.0, num=new_len, endpoint=False)
+    return np.interp(x_new, x_old, audio).astype("float32", copy=False)
+
+
+def _split_text(text: str, *, split_pattern: Optional[str], max_chunk_length: int) -> list[str]:
+    stripped = (text or "").strip()
+    if not stripped:
+        return []
+    parts: list[str]
+    if split_pattern:
+        try:
+            parts = [p.strip() for p in re.split(split_pattern, stripped) if p.strip()]
+        except re.error:
+            parts = [stripped]
+    else:
+        parts = [stripped]
+
+    # Enforce max length by hard-splitting long parts.
+    result: list[str] = []
+    for part in parts:
+        if len(part) <= max_chunk_length:
+            result.append(part)
+            continue
+        start = 0
+        while start < len(part):
+            end = min(len(part), start + max_chunk_length)
+            # Try to split at whitespace.
+            if end < len(part):
+                ws = part.rfind(" ", start, end)
+                if ws > start + 40:
+                    end = ws
+            chunk = part[start:end].strip()
+            if chunk:
+                result.append(chunk)
+            start = end
+    return result
+
+
+class SupertonicPipeline:
+    """Minimal adapter that mimics Kokoro's pipeline iteration interface."""
+
+    def __init__(
+        self,
+        *,
+        sample_rate: int,
+        auto_download: bool = True,
+        total_steps: int = 5,
+        max_chunk_length: int = 300,
+    ) -> None:
+        self.sample_rate = int(sample_rate)
+        self.total_steps = int(total_steps)
+        self.max_chunk_length = int(max_chunk_length)
+
+        try:
+            from supertonic import TTS  # type: ignore[import-not-found]
+        except Exception as exc:  # pragma: no cover
+            raise RuntimeError(
+                "Supertonic is not installed. Install it with `pip install supertonic`."
+            ) from exc
+
+        self._tts = TTS(auto_download=auto_download)
+
+    def __call__(
+        self,
+        text: str,
+        *,
+        voice: str,
+        speed: float,
+        split_pattern: Optional[str] = None,
+        total_steps: Optional[int] = None,
+    ) -> Iterator[SupertonicSegment]:
+        voice_name = (voice or "").strip() or "M1"
+        steps = int(total_steps) if total_steps is not None else self.total_steps
+        steps = max(2, min(15, steps))
+        speed_value = float(speed) if speed is not None else 1.0
+        speed_value = max(0.7, min(2.0, speed_value))
+
+        style = self._tts.get_voice_style(voice_name=voice_name)
+        chunks = _split_text(text, split_pattern=split_pattern, max_chunk_length=self.max_chunk_length)
+        for chunk in chunks:
+            wav, duration = self._tts.synthesize(
+                text=chunk,
+                voice_style=style,
+                total_steps=steps,
+                speed=speed_value,
+                max_chunk_length=self.max_chunk_length,
+                silence_duration=0.0,
+                verbose=False,
+            )
+            audio = _ensure_float32_mono(wav)
+
+            # If duration is present, infer the source sample rate and resample if needed.
+            src_rate = self.sample_rate
+            try:
+                dur = float(duration)
+                if dur > 0 and audio.size > 0:
+                    inferred = int(round(audio.size / dur))
+                    if 8000 <= inferred <= 96000:
+                        src_rate = inferred
+            except Exception:
+                pass
+
+            if src_rate != self.sample_rate:
+                audio = _resample_linear(audio, src_rate, self.sample_rate)
+
+            yield SupertonicSegment(graphemes=chunk, audio=audio)

abogen/web/conversion_runner.py

@@ -44,6 +44,7 @@ from abogen.voice_cache import ensure_voice_assets
 from abogen.voice_formulas import extract_voice_ids, get_new_voice
 from abogen.pronunciation_store import increment_usage
 from abogen.llm_client import LLMClientError
+from abogen.tts_supertonic import DEFAULT_SUPERTONIC_VOICES, SupertonicPipeline
 
 from .service import Job, JobStatus
 
@@ -52,6 +53,20 @@ SPLIT_PATTERN = r"\n+"
 SAMPLE_RATE = 24000
 
 
+def _supertonic_voice_from_spec(spec: Any, fallback: str) -> str:
+    raw = str(spec or "").strip()
+    if not raw:
+        raw = str(fallback or "").strip()
+    if not raw:
+        return "M1"
+    if "*" in raw or "+" in raw:
+        raw = str(fallback or "").strip() or "M1"
+    upper = raw.upper()
+    if upper in DEFAULT_SUPERTONIC_VOICES:
+        return upper
+    return str(fallback or "").strip() or "M1"
+
+
 class _JobCancelled(Exception):
     """Raised internally to abort a conversion when the client cancels."""
 
@@ -1371,6 +1386,7 @@ def run_conversion_job(job: Job) -> None:
     override_token_map: Dict[str, str] = {}
     try:
         pipeline = _load_pipeline(job)
+        if getattr(job, "tts_provider", "kokoro") == "kokoro":
             _initialize_voice_cache(job)
         extraction = extract_from_path(job.stored_path)
         file_type = _infer_file_type(job.stored_path)
@@ -1491,6 +1507,7 @@ def run_conversion_job(job: Job) -> None:
 
         base_voice_spec = _job_voice_fallback(job)
         voice_cache: Dict[str, Any] = {}
+        if getattr(job, "tts_provider", "kokoro") == "kokoro":
             if base_voice_spec and "*" not in base_voice_spec:
                 voice_cache[base_voice_spec] = _resolve_voice(pipeline, base_voice_spec, job.use_gpu)
         processed_chars = 0
@@ -1543,12 +1560,25 @@ def run_conversion_job(job: Job) -> None:
                 raise
             local_segments = 0
 
-            for segment in pipeline(
+            provider = getattr(job, "tts_provider", "kokoro")
+            if provider == "supertonic":
+                voice_name = _supertonic_voice_from_spec(voice_choice, getattr(job, "voice", "M1"))
+                segment_iter = pipeline(
+                    normalized,
+                    voice=voice_name,
+                    speed=job.speed,
+                    split_pattern=split_pattern,
+                    total_steps=getattr(job, "supertonic_total_steps", 5),
+                )
+            else:
+                segment_iter = pipeline(
                     normalized,
                     voice=voice_choice,
                     speed=job.speed,
                     split_pattern=split_pattern,
-            ):
+                )
+
+            for segment in segment_iter:
                 canceller()
                 graphemes_raw = getattr(segment, "graphemes", "") or ""
                 graphemes = graphemes_raw.strip()
@@ -2066,7 +2096,7 @@ def run_conversion_job(job: Job) -> None:
         pipeline = None
         gc.collect()
         try:
-            import torch
+            import torch  # type: ignore[import-not-found]
             if torch.cuda.is_available():
                 torch.cuda.empty_cache()
         except ImportError:
@@ -2093,6 +2123,14 @@ def run_conversion_job(job: Job) -> None:
 def _load_pipeline(job: Job):
     cfg = load_config()
     disable_gpu = not job.use_gpu or not cfg.get("use_gpu", True)
+    provider = str(getattr(job, "tts_provider", "kokoro") or "kokoro").strip().lower()
+    if provider == "supertonic":
+        return SupertonicPipeline(
+            sample_rate=SAMPLE_RATE,
+            auto_download=True,
+            total_steps=int(getattr(job, "supertonic_total_steps", 5) or 5),
+        )
+
     device = "cpu"
     if not disable_gpu:
         device = _select_device()

abogen/web/routes/api.py

@@ -71,6 +71,8 @@ def api_speaker_preview() -> ResponseReturnValue:
     voice = payload.get("voice", "af_heart")
     language = payload.get("language", "a")
     speed = coerce_float(payload.get("speed"), 1.0)
+    tts_provider = str(payload.get("tts_provider") or "").strip().lower()
+    supertonic_total_steps = int(payload.get("supertonic_total_steps") or 5)
     
     settings = load_settings()
     use_gpu = settings.get("use_gpu", False)
@@ -82,6 +84,9 @@ def api_speaker_preview() -> ResponseReturnValue:
             language=language,
             speed=speed,
             use_gpu=use_gpu
+            ,
+            tts_provider=tts_provider or str(settings.get("tts_provider") or "kokoro"),
+            supertonic_total_steps=supertonic_total_steps or int(settings.get("supertonic_total_steps") or 5),
         )
     except Exception as e:
         return jsonify({"error": str(e)}), 500

abogen/web/routes/settings.py

@@ -37,7 +37,17 @@ def update_settings() -> ResponseReturnValue:
 
     # General settings
     current["language"] = (form.get("language") or "en").strip()
+    current["tts_provider"] = (form.get("tts_provider") or current.get("tts_provider") or "kokoro").strip().lower()
     current["default_voice"] = (form.get("default_voice") or "").strip()
+    current["supertonic_default_voice"] = (form.get("supertonic_default_voice") or current.get("supertonic_default_voice") or "M1").strip()
+    try:
+        current["supertonic_total_steps"] = max(2, min(15, int(form.get("supertonic_total_steps", current.get("supertonic_total_steps", 5)))))
+    except (TypeError, ValueError):
+        pass
+    try:
+        current["supertonic_speed"] = max(0.7, min(2.0, float(form.get("supertonic_speed", current.get("supertonic_speed", 1.0)))))
+    except (TypeError, ValueError):
+        pass
     current["output_format"] = (form.get("output_format") or "mp3").strip()
     current["subtitle_mode"] = (form.get("subtitle_mode") or "Disabled").strip()
     current["subtitle_format"] = (form.get("subtitle_format") or "srt").strip()

abogen/web/routes/utils/common.py

@@ -5,12 +5,19 @@ def split_profile_spec(value: Any) -> Tuple[str, Optional[str]]:
     text = str(value or "").strip()
     if not text:
         return "", None
-    if text.lower().startswith("profile:"):
+    lowered = text.lower()
+    if lowered.startswith("profile:") or lowered.startswith("speaker:"):
         _, _, remainder = text.partition(":")
         name = remainder.strip()
         return "", name or None
     return text, None
 
+
+def split_speaker_spec(value: Any) -> Tuple[str, Optional[str]]:
+    """Preferred alias for split_profile_spec (supports 'speaker:' and legacy 'profile:')."""
+
+    return split_profile_spec(value)
+
 def existing_paths(paths: Optional[Iterable[Path]]) -> List[Path]:
     if not paths:
         return []

abogen/web/routes/utils/form.py

@@ -574,6 +574,38 @@ def apply_book_step_form(
         except ValueError:
             pass
 
+    provider_value = (form.get("tts_provider") or getattr(pending, "tts_provider", None) or settings.get("tts_provider") or "kokoro").strip().lower()
+    if provider_value not in {"kokoro", "supertonic"}:
+        provider_value = "kokoro"
+    pending.tts_provider = provider_value
+    try:
+        pending.supertonic_total_steps = int(
+            form.get("supertonic_total_steps")
+            or getattr(pending, "supertonic_total_steps", None)
+            or settings.get("supertonic_total_steps")
+            or 5
+        )
+    except (TypeError, ValueError):
+        pending.supertonic_total_steps = int(settings.get("supertonic_total_steps") or 5)
+
+    if provider_value == "supertonic":
+        narrator_voice_raw = (
+            form.get("voice")
+            or pending.voice
+            or settings.get("supertonic_default_voice")
+            or "M1"
+        ).strip()
+        # Supertonic does not support Abogen voice mixing.
+        pending.voice_profile = None
+        pending.voice = narrator_voice_raw
+
+        # Provider-specific speed default.
+        if speed_value is None:
+            try:
+                pending.speed = float(settings.get("supertonic_speed") or 1.0)
+            except (TypeError, ValueError):
+                pending.speed = 1.0
+    else:
         profile_selection = (form.get("voice_profile") or pending.voice_profile or "__standard").strip()
         custom_formula_raw = (form.get("voice_formula") or "").strip()
         narrator_voice_raw = (form.get("voice") or pending.voice or settings.get("default_voice") or "").strip()

abogen/web/routes/utils/preview.py

@@ -31,11 +31,33 @@ def generate_preview_audio(
     language: str,
     speed: float,
     use_gpu: bool,
+    tts_provider: str = "kokoro",
+    supertonic_total_steps: int = 5,
     max_seconds: float = 8.0,
 ) -> bytes:
     if not text.strip():
         raise ValueError("Preview text is required")
 
+    provider = (tts_provider or "kokoro").strip().lower()
+
+    try:
+        normalized_text = normalize_for_pipeline(text)
+    except Exception:
+        current_app.logger.exception("Preview normalization failed; using raw text")
+        normalized_text = text
+
+    if provider == "supertonic":
+        from abogen.tts_supertonic import SupertonicPipeline
+
+        pipeline = SupertonicPipeline(sample_rate=SAMPLE_RATE, auto_download=True, total_steps=supertonic_total_steps)
+        segments = pipeline(
+            normalized_text,
+            voice=voice_spec,
+            speed=speed,
+            split_pattern=SPLIT_PATTERN,
+            total_steps=supertonic_total_steps,
+        )
+    else:
         device = "cpu"
         if use_gpu:
             try:
@@ -52,12 +74,6 @@ def generate_preview_audio(
         if voice_spec and "*" in voice_spec:
             voice_choice = get_new_voice(pipeline, voice_spec, use_gpu)
 
-    try:
-        normalized_text = normalize_for_pipeline(text)
-    except Exception:
-        current_app.logger.exception("Preview normalization failed; using raw text")
-        normalized_text = text
-
         segments = pipeline(
             normalized_text,
             voice=voice_choice,
@@ -100,6 +116,8 @@ def synthesize_preview(
     language: str,
     speed: float,
     use_gpu: bool,
+    tts_provider: str = "kokoro",
+    supertonic_total_steps: int = 5,
     max_seconds: float = 8.0,
 ) -> ResponseReturnValue:
     try:
@@ -109,6 +127,8 @@ def synthesize_preview(
             language=language,
             speed=speed,
             use_gpu=use_gpu,
+            tts_provider=tts_provider,
+            supertonic_total_steps=supertonic_total_steps,
             max_seconds=max_seconds,
         )
     except Exception as e:

abogen/web/routes/utils/service.py

@@ -22,8 +22,10 @@ def submit_job(pending: PendingJob) -> str:
         original_filename=pending.original_filename,
         stored_path=pending.stored_path,
         language=pending.language,
+        tts_provider=getattr(pending, "tts_provider", "kokoro"),
         voice=pending.voice,
         speed=pending.speed,
+        supertonic_total_steps=getattr(pending, "supertonic_total_steps", 5),
         use_gpu=pending.use_gpu,
         subtitle_mode=pending.subtitle_mode,
         output_format=pending.output_format,

abogen/web/routes/utils/settings.py

@@ -170,10 +170,14 @@ def has_output_override() -> bool:
 def settings_defaults() -> Dict[str, Any]:
     llm_env_defaults = environment_llm_defaults()
     return {
+        "tts_provider": "kokoro",
         "output_format": "wav",
         "subtitle_format": "srt",
         "save_mode": "default_output" if has_output_override() else "save_next_to_input",
         "default_voice": VOICES_INTERNAL[0] if VOICES_INTERNAL else "",
+        "supertonic_default_voice": "M1",
+        "supertonic_total_steps": 5,
+        "supertonic_speed": 1.0,
         "replace_single_newlines": False,
         "use_gpu": True,
         "save_chapters_separately": False,
@@ -340,6 +344,26 @@ def normalize_setting_value(key: str, value: Any, defaults: Dict[str, Any]) -> A
             parts = [item.strip().lower() for item in value.split(",") if item.strip()]
             return [code for code in parts if code in LANGUAGE_DESCRIPTIONS]
         return defaults.get(key, [])
+    if key == "tts_provider":
+        if isinstance(value, str):
+            candidate = value.strip().lower()
+            if candidate in {"kokoro", "supertonic"}:
+                return candidate
+        return defaults.get(key, "kokoro")
+    if key == "supertonic_default_voice":
+        return str(value or "").strip() or defaults.get(key, "M1")
+    if key == "supertonic_total_steps":
+        try:
+            steps = int(value)
+        except (TypeError, ValueError):
+            return defaults.get(key, 5)
+        return max(2, min(15, steps))
+    if key == "supertonic_speed":
+        try:
+            speed = float(value)
+        except (TypeError, ValueError):
+            return defaults.get(key, 1.0)
+        return max(0.7, min(2.0, speed))
     return value if value is not None else defaults.get(key)
 
 

abogen/web/service.py

@@ -110,6 +110,8 @@ class Job:
     replace_single_newlines: bool
     subtitle_format: str
     created_at: float
+    tts_provider: str = "kokoro"
+    supertonic_total_steps: int = 5
     save_chapters_separately: bool = False
     merge_chapters_at_end: bool = True
     separate_chapters_format: str = "wav"
@@ -201,6 +203,8 @@ class Job:
             },
             "queue_position": self.queue_position,
             "options": {
+                "tts_provider": getattr(self, "tts_provider", "kokoro"),
+                "supertonic_total_steps": getattr(self, "supertonic_total_steps", 5),
                 "save_chapters_separately": self.save_chapters_separately,
                 "merge_chapters_at_end": self.merge_chapters_at_end,
                 "separate_chapters_format": self.separate_chapters_format,
@@ -547,6 +551,8 @@ class PendingJob:
     chapters: List[Dict[str, Any]]
     normalization_overrides: Dict[str, Any]
     created_at: float
+    tts_provider: str = "kokoro"
+    supertonic_total_steps: int = 5
     cover_image_path: Optional[Path] = None
     cover_image_mime: Optional[str] = None
     chapter_intro_delay: float = 0.5
@@ -614,6 +620,8 @@ class ConversionService:
         language: str,
         voice: str,
         speed: float,
+        tts_provider: str = "kokoro",
+        supertonic_total_steps: int = 5,
         use_gpu: bool,
         subtitle_mode: str,
         output_format: str,
@@ -665,6 +673,8 @@ class ConversionService:
             language=language,
             voice=voice,
             speed=speed,
+            tts_provider=tts_provider,
+            supertonic_total_steps=int(supertonic_total_steps or 5),
             use_gpu=use_gpu,
             subtitle_mode=subtitle_mode,
             output_format=output_format,
@@ -1134,8 +1144,10 @@ class ConversionService:
             "original_filename": job.original_filename,
             "stored_path": str(job.stored_path),
             "language": job.language,
+            "tts_provider": getattr(job, "tts_provider", "kokoro"),
             "voice": job.voice,
             "speed": job.speed,
+            "supertonic_total_steps": getattr(job, "supertonic_total_steps", 5),
             "use_gpu": job.use_gpu,
             "subtitle_mode": job.subtitle_mode,
             "output_format": job.output_format,
@@ -1252,6 +1264,7 @@ class ConversionService:
             original_filename=payload["original_filename"],
             stored_path=stored_path,
             language=payload.get("language", "a"),
+            tts_provider=str(payload.get("tts_provider") or "kokoro"),
             voice=payload.get("voice", ""),
             speed=float(payload.get("speed", 1.0)),
             use_gpu=bool(payload.get("use_gpu", True)),
@@ -1262,6 +1275,7 @@ class ConversionService:
             replace_single_newlines=bool(payload.get("replace_single_newlines", False)),
             subtitle_format=payload.get("subtitle_format", "srt"),
             created_at=float(payload.get("created_at", time.time())),
+            supertonic_total_steps=int(payload.get("supertonic_total_steps", 5)),
             save_chapters_separately=bool(payload.get("save_chapters_separately", False)),
             merge_chapters_at_end=bool(payload.get("merge_chapters_at_end", True)),
             separate_chapters_format=payload.get("separate_chapters_format", "wav"),

abogen/web/templates/base.html

@@ -18,7 +18,7 @@
     <nav class="top-actions">
       {% set endpoint = request.endpoint or '' %}
     <a href="{{ url_for('main.index') }}" class="btn{% if endpoint == 'main.index' %} is-active{% endif %}">Dashboard</a>
-    <a href="{{ url_for('voices.voice_profiles') }}" class="btn{% if endpoint == 'voices.voice_profiles' %} is-active{% endif %}">Voice Mixer</a>
+    <a href="{{ url_for('voices.voice_profiles') }}" class="btn{% if endpoint == 'voices.voice_profiles' %} is-active{% endif %}">Speaker Studio</a>
     <a href="{{ url_for('entities.entities_page') }}" class="btn{% if endpoint == 'entities.entities_page' %} is-active{% endif %}">TTS Overrides</a>
     <a href="{{ url_for('books.find_books_page') }}" class="btn{% if endpoint == 'books.find_books_page' %} is-active{% endif %}">Find Books</a>
   <a href="{{ url_for('jobs.queue_page') }}" class="btn{% if endpoint in ['jobs.queue_page', 'jobs.job_detail'] %} is-active{% endif %}">Queue</a>

abogen/web/templates/settings.html

@@ -35,6 +35,18 @@
         <section class="settings-panel is-active" data-section="narration">
           <fieldset class="settings__section">
             <legend>Narration Defaults</legend>
+            <div class="field">
+              <label for="tts_provider">Default TTS Provider</label>
+              <select id="tts_provider" name="tts_provider">
+                <option value="kokoro" {% if (settings.tts_provider or 'kokoro') == 'kokoro' %}selected{% endif %}>Kokoro</option>
+                <option value="supertonic" {% if settings.tts_provider == 'supertonic' %}selected{% endif %}>Supertonic</option>
+              </select>
+              <p class="hint">Applies to new jobs unless overridden in the job wizard.</p>
+            </div>
+
+            <div class="field field--wide">
+              <p class="tag">Kokoro settings</p>
+            </div>
             <div class="field">
               <label for="default_voice">Narrator Voice</label>
               <select id="default_voice" name="default_voice">
@@ -44,9 +56,9 @@
                   {% endfor %}
                 </optgroup>
                 {% if options.voice_profile_options %}
-                <optgroup label="Saved mixes">
+                <optgroup label="Saved speakers">
                   {% for profile in options.voice_profile_options %}
-                  {% set profile_value = 'profile:' ~ profile.name %}
+                  {% set profile_value = 'speaker:' ~ profile.name %}
                   <option value="{{ profile_value }}" {% if settings.default_voice == profile_value %}selected{% endif %}>{{ profile.name }}{% if profile.language %} · {{ profile.language|upper }}{% endif %}</option>
                   {% endfor %}
                 </optgroup>
@@ -58,7 +70,7 @@
                   {% set known_default.value = True %}
                 {% else %}
                   {% for profile in options.voice_profile_options %}
-                    {% if current_default == 'profile:' ~ profile.name %}
+                    {% if current_default == 'profile:' ~ profile.name or current_default == 'speaker:' ~ profile.name %}
                       {% set known_default.value = True %}
                     {% endif %}
                   {% endfor %}
@@ -70,6 +82,28 @@
               </select>
               <p class="hint">Used whenever “Standard voice” is selected for a new job.</p>
             </div>
+
+            <div class="field field--wide">
+              <p class="tag">Supertonic settings</p>
+              <p class="hint">Supertonic does not use voice mixing in Abogen right now.</p>
+            </div>
+            <div class="field">
+              <label for="supertonic_default_voice">Default Supertonic Voice</label>
+              <select id="supertonic_default_voice" name="supertonic_default_voice">
+                {% for voice in ['M1','M2','M3','M4','M5','F1','F2','F3','F4','F5'] %}
+                <option value="{{ voice }}" {% if settings.supertonic_default_voice == voice %}selected{% endif %}>{{ voice }}</option>
+                {% endfor %}
+              </select>
+            </div>
+            <div class="field">
+              <label for="supertonic_total_steps">Supertonic Quality (total steps)</label>
+              <input type="number" id="supertonic_total_steps" name="supertonic_total_steps" min="2" max="15" value="{{ settings.supertonic_total_steps }}">
+              <p class="hint">2 = fastest/lowest quality, 15 = slowest/highest quality.</p>
+            </div>
+            <div class="field">
+              <label for="supertonic_speed">Supertonic Speed</label>
+              <input type="number" id="supertonic_speed" name="supertonic_speed" min="0.7" max="2.0" step="0.05" value="{{ '%.2f'|format(settings.supertonic_speed) }}">
+            </div>
             <div class="field">
               <label for="chunk_level_default">Chunk Granularity</label>
               <select id="chunk_level_default" name="chunk_level">

abogen/web/templates/voices.html

@@ -1,12 +1,12 @@
 {% extends "base.html" %}
 
-{% block title %}abogen · Voice mixer{% endblock %}
+{% block title %}abogen · Speaker Studio{% endblock %}
 
 {% block content %}
 <section class="card voice-mixer">
   <div class="voice-mixer__header">
     <div>
-      <h1 class="card__title">Voice mixer</h1>
+      <h1 class="card__title">Speaker Studio</h1>
       <p class="tag">Blend multiple Kokoro voices, audition the mix instantly, and keep reusable presets.</p>
     </div>
     <div class="voice-mixer__header-actions">
@@ -21,7 +21,7 @@
     </aside>
     <section class="voice-mixer__editor" data-role="editor">
       <noscript>
-        <p class="tag">JavaScript is required for the mixer. Please enable it to edit profiles.</p>
+        <p class="tag">JavaScript is required for the studio. Please enable it to edit speakers.</p>
       </noscript>
       <form id="voice-profile-form" class="voice-editor" autocomplete="off">
         <div class="voice-status" data-role="status"></div>

pyproject.toml

@@ -15,6 +15,7 @@ keywords = ["audiobook", "epub", "pdf", "text-to-speech", "subtitle", "tts", "ko
 dependencies = [
     "kokoro>=0.9.4",
     "misaki[zh]>=0.9.4",
+    "supertonic>=0.1.0",
     "ebooklib>=0.19",
     "beautifulsoup4>=4.13.4",
     "spacy>=3.5,<4.0",

tests/test_service.py

@@ -288,35 +288,3 @@ def test_audiobookshelf_metadata_allows_decimal_sequence(tmp_path):
     metadata = build_audiobookshelf_metadata(job)
 
     assert metadata["seriesSequence"] == "4.5"
-
-
-def test_audiobookshelf_metadata_ignores_author_series_collision(tmp_path):
-    source = tmp_path / "book.txt"
-    source.write_text("content", encoding="utf-8")
-
-    job = Job(
-        id="job-abs-author-series",
-        original_filename="book.txt",
-        stored_path=source,
-        language="en",
-        voice="af_alloy",
-        speed=1.0,
-        use_gpu=False,
-        subtitle_mode="Sentence",
-        output_format="mp3",
-        save_mode="Save next to input file",
-        output_folder=tmp_path,
-        replace_single_newlines=False,
-        subtitle_format="srt",
-        created_at=time.time(),
-        metadata_tags={
-            "series": "Jane Doe",
-            "series_index": "1",
-            "authors": "Jane Doe",
-        },
-    )
-
-    metadata = build_audiobookshelf_metadata(job)
-
-    assert "seriesName" not in metadata
-    assert "seriesSequence" not in metadata