mirror of
https://github.com/denizsafak/abogen.git
synced 2026-07-18 05:40:26 +02:00
feat: Enhance speaker analysis with gender inference and update related tests
This commit is contained in:
JB
@@ -36,3 +36,4 @@ storage/
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build/
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dist/
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.old/
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test_assets/
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@@ -28,14 +28,16 @@ _DIALOGUE_VERBS = (
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)
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_VERB_PATTERN = "(?:" + "|".join(_DIALOGUE_VERBS) + ")"
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_NAME_FRAGMENT = r"[A-Z][A-Za-z'\-]+"
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_NAME_FRAGMENT = r"[A-ZÀ-ÖØ-Þ][\w'’\-]*"
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_NAME_PATTERN = rf"{_NAME_FRAGMENT}(?:\s+{_NAME_FRAGMENT})*"
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_COLON_PATTERN = re.compile(rf"^\s*({_NAME_PATTERN})\s*:\s*(.+)$")
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_NAME_BEFORE_VERB = re.compile(rf"({_NAME_PATTERN})\s+{_VERB_PATTERN}\b", re.IGNORECASE)
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_VERB_BEFORE_NAME = re.compile(rf"{_VERB_PATTERN}\s+({_NAME_PATTERN})", re.IGNORECASE)
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_PRONOUN_PATTERN = re.compile(r"\b(?:he|she|they)\b", re.IGNORECASE)
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_QUOTE_PATTERN = re.compile(r'"([^"\\]*(?:\\.[^"\\]*)*)"')
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_QUOTE_PATTERN = re.compile(r'["“”]([^"“”\\]*(?:\\.[^"“”\\]*)*)["”]')
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_MALE_PRONOUN_PATTERN = re.compile(r"\b(?:he|him|his|himself)\b", re.IGNORECASE)
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_FEMALE_PRONOUN_PATTERN = re.compile(r"\b(?:she|her|hers|herself)\b", re.IGNORECASE)
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_CONFIDENCE_RANK = {"low": 1, "medium": 2, "high": 3}
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@@ -48,6 +50,9 @@ class SpeakerGuess:
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confidence: str = "low"
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sample_quotes: List[str] = field(default_factory=list)
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suppressed: bool = False
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gender: str = "unknown"
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male_votes: int = 0
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female_votes: int = 0
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def register_occurrence(self, confidence: str, quote: Optional[str]) -> None:
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self.count += 1
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@@ -60,6 +65,13 @@ class SpeakerGuess:
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if len(self.sample_quotes) > 3:
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self.sample_quotes = self.sample_quotes[:3]
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def register_gender(self, male_votes: int, female_votes: int) -> None:
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if male_votes:
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self.male_votes += male_votes
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if female_votes:
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self.female_votes += female_votes
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self.gender = _derive_gender(self.male_votes, self.female_votes, self.gender)
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def as_dict(self) -> Dict[str, Any]:
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return {
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"id": self.speaker_id,
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@@ -68,6 +80,7 @@ class SpeakerGuess:
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"confidence": self.confidence,
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"sample_quotes": list(self.sample_quotes),
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"suppressed": self.suppressed,
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"gender": self.gender,
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}
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@@ -131,14 +144,23 @@ def analyze_speakers(
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assignments[chunk_id] = speaker_id
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unique_speakers.add(speaker_id)
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label = _normalize_label(speaker_id)
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record_id = label_index.get(label)
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if record_id is None:
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record_id = _dedupe_slug(_slugify(label), speaker_guesses)
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label_index[label] = record_id
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speaker_guesses[record_id] = SpeakerGuess(speaker_id=record_id, label=label)
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guess = speaker_guesses[record_id]
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male_votes, female_votes = _count_gender_votes(text)
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if speaker_id in speaker_guesses:
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record_id = speaker_id
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guess = speaker_guesses[record_id]
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label = guess.label
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else:
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label = _normalize_label(speaker_id)
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record_id = label_index.get(label)
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if record_id is None:
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record_id = _dedupe_slug(_slugify(label), speaker_guesses)
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label_index[label] = record_id
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speaker_guesses[record_id] = SpeakerGuess(speaker_id=record_id, label=label)
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guess = speaker_guesses[record_id]
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guess.register_occurrence(confidence, quote)
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if record_id != narrator_id and (male_votes or female_votes):
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guess.register_gender(male_votes, female_votes)
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if record_id != speaker_id:
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# Maintain mapping to canonical ID in assignments.
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assignments[chunk_id] = record_id
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@@ -294,3 +316,28 @@ def _reassign(assignments: Dict[str, str], old: str, new: str) -> None:
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for key, value in list(assignments.items()):
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if value == old:
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assignments[key] = new
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def _count_gender_votes(text: str) -> Tuple[int, int]:
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if not text:
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return 0, 0
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male = len(_MALE_PRONOUN_PATTERN.findall(text))
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female = len(_FEMALE_PRONOUN_PATTERN.findall(text))
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return male, female
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def _derive_gender(male_votes: int, female_votes: int, current: str) -> str:
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if male_votes == 0 and female_votes == 0:
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return current if current != "unknown" else "unknown"
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male_threshold = max(2, female_votes + 1)
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female_threshold = max(2, male_votes + 1)
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if male_votes >= male_threshold:
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return "male"
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if female_votes >= female_threshold:
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return "female"
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if current in {"male", "female"}:
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return current
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return "unknown"
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+22
-13
@@ -8,7 +8,7 @@ import textwrap
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import urllib.parse
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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from typing import Any, Dict, Iterable, List, Optional, Tuple, cast
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import ebooklib # type: ignore[import]
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import fitz # type: ignore[import]
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@@ -16,7 +16,7 @@ import markdown # type: ignore[import]
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from bs4 import BeautifulSoup, NavigableString # type: ignore[import]
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from ebooklib import epub # type: ignore[import]
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from .utils import clean_text, detect_encoding
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from .utils import calculate_text_length, clean_text, detect_encoding
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logger = logging.getLogger(__name__)
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@@ -45,7 +45,7 @@ class ExtractedChapter:
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@property
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def characters(self) -> int:
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return len(self.text)
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return calculate_text_length(self.text)
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@dataclass
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@@ -192,7 +192,7 @@ def _build_metadata_payload(
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"ALBUM": title,
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"YEAR": metadata_source.publication_year or now_year,
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"ALBUM_ARTIST": authors_text,
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"COMPOSER": "Narrator",
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"COMPOSER": authors_text,
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"GENRE": "Audiobook",
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"CHAPTER_COUNT": str(chapter_count),
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}
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@@ -213,8 +213,10 @@ def _extract_pdf(path: Path) -> ExtractionResult:
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chapters: List[ExtractedChapter] = []
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with fitz.open(str(path)) as document:
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metadata_source = _collect_pdf_metadata(document)
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for index, page in enumerate(document):
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text = _clean_pdf_text(page.get_text())
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pages = cast(Iterable[fitz.Page], document)
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for index, page in enumerate(pages):
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page_obj = cast(Any, page)
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text = _clean_pdf_text(page_obj.get_text())
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if not text:
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continue
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title = f"Page {index + 1}"
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@@ -544,8 +546,8 @@ class EpubExtractor:
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chapters.append(ExtractedChapter(title=title, text=text))
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return chapters
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def _find_navigation_item(self) -> Tuple[Optional[ebooklib.epub.EpubItem], Optional[str]]:
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nav_item: Optional[ebooklib.epub.EpubItem] = None
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def _find_navigation_item(self) -> Tuple[Optional[epub.EpubItem], Optional[str]]:
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nav_item: Optional[epub.EpubItem] = None
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nav_type: Optional[str] = None
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nav_items = list(self.book.get_items_of_type(ebooklib.ITEM_NAVIGATION))
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@@ -621,12 +623,14 @@ class EpubExtractor:
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for content_node in nav_soup.find_all("content"):
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src = content_node.get("src")
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if src:
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targets.append(src.split("#", 1)[0])
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src_value = str(src)
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targets.append(src_value.split("#", 1)[0])
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else:
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for link in nav_soup.find_all("a"):
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href = link.get("href")
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if href:
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targets.append(href.split("#", 1)[0])
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href_value = str(href)
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targets.append(href_value.split("#", 1)[0])
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return targets
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def _cache_relevant_documents(self, doc_order: Dict[str, int], nav_targets: List[str]) -> None:
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@@ -896,11 +900,16 @@ class EpubExtractor:
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for tag in soup.find_all(["p", "div"]):
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tag.append("\n\n")
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for ol in soup.find_all("ol"):
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start = int(ol.get("start", 1))
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start_attr = ol.get("start")
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try:
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start = int(str(start_attr)) if start_attr is not None else 1
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except (TypeError, ValueError):
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start = 1
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for idx, li in enumerate(ol.find_all("li", recursive=False)):
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number_text = f"{start + idx}) "
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if li.string:
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li.string.replace_with(number_text + li.string)
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existing = li.string
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if isinstance(existing, NavigableString):
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existing.replace_with(NavigableString(number_text + str(existing)))
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else:
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li.insert(0, NavigableString(number_text))
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for tag in soup.find_all(["sup", "sub"]):
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@@ -332,7 +332,7 @@ def _apply_prepare_form(
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"text": chapter.get("text", ""),
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"enabled": enabled,
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}
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entry["characters"] = len(entry["text"])
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entry["characters"] = calculate_text_length(entry["text"])
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if enabled:
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if voice_selection.startswith("voice:"):
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@@ -359,7 +359,7 @@ def _apply_prepare_form(
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else:
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entry["voice_formula"] = formula_input
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entry["resolved_voice"] = formula_input
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selected_total += len(entry["text"] or "")
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selected_total += entry["characters"]
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overrides.append(entry)
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pending.chapters[index] = dict(entry)
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@@ -1299,7 +1299,7 @@ def enqueue_job() -> ResponseReturnValue:
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"index": index,
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"title": chapter.title,
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"text": chapter.text,
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"characters": len(chapter.text),
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"characters": calculate_text_length(chapter.text),
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"enabled": enabled,
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}
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)
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@@ -113,6 +113,7 @@ body {
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box-shadow: 0 20px 50px rgba(8, 15, 32, 0.35);
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position: relative;
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overflow: hidden;
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z-index: 0;
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}
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.card::before {
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@@ -121,6 +122,7 @@ body {
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inset: 0;
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background: radial-gradient(circle at 0% 0%, rgba(56, 189, 248, 0.15), transparent 55%);
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pointer-events: none;
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z-index: -1;
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}
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.card__title {
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@@ -142,11 +144,17 @@ body {
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align-items: start;
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}
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.form-grid {
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grid-template-columns: minmax(0, 420px) minmax(0, 1fr);
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align-items: start;
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gap: 2rem;
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}
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.form-grid > .grid {
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align-items: start;
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max-width: 460px;
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width: min(100%, 460px);
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justify-self: start;
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max-width: none;
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width: 100%;
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justify-self: stretch;
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}
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.button {
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@@ -650,29 +658,50 @@ body {
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.prepare-summary {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(220px, 1fr));
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gap: 1.5rem;
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margin-bottom: 1.5rem;
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grid-template-columns: minmax(0, 320px) minmax(0, 1fr);
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gap: 2rem;
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margin-bottom: 2rem;
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align-items: start;
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}
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.prepare-summary dl {
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.prepare-summary__stats dl {
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margin: 0;
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display: grid;
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gap: 0.6rem;
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grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
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}
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.prepare-summary dt {
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.prepare-summary__stats dt {
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font-size: 0.75rem;
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letter-spacing: 0.04em;
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text-transform: uppercase;
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color: var(--muted);
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}
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.prepare-summary dd {
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.prepare-summary__stats dd {
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margin: 0;
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font-weight: 500;
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}
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.prepare-summary__insights {
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display: grid;
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gap: 1.25rem;
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align-content: start;
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}
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.prepare-summary__stats dl > div {
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display: grid;
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gap: 0.25rem;
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}
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.prepare-summary__insights > .prepare-analysis,
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.prepare-summary__insights > .prepare-metadata {
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border: 1px solid rgba(148, 163, 184, 0.2);
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background: rgba(15, 23, 42, 0.35);
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border-radius: 18px;
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padding: 1rem 1.25rem;
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}
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.prepare-speakers {
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margin-top: 2rem;
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border-top: 1px solid var(--panel-border);
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@@ -918,6 +947,26 @@ body {
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color: var(--accent);
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}
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@media (max-width: 1024px) {
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.prepare-summary {
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grid-template-columns: 1fr;
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}
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.prepare-summary__stats dl {
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grid-template-columns: repeat(auto-fit, minmax(160px, 1fr));
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}
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}
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||||
@media (max-width: 880px) {
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.form-grid {
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grid-template-columns: 1fr;
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}
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||||
|
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.voice-preview {
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width: 100%;
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}
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}
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||||
|
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.hint {
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margin: 0;
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font-size: 0.8rem;
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@@ -1481,9 +1530,10 @@ progress.progress::-moz-progress-bar {
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||||
gap: 0.9rem;
|
||||
padding: 1rem 1.25rem;
|
||||
border-radius: 18px;
|
||||
border: 1px solid rgba(148, 163, 184, 0.18);
|
||||
background: rgba(15, 23, 42, 0.35);
|
||||
max-width: 460px;
|
||||
border: 1px solid rgba(148, 163, 184, 0.22);
|
||||
background: rgba(15, 23, 42, 0.6);
|
||||
box-shadow: 0 16px 40px rgba(8, 15, 32, 0.45);
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||||
width: min(100%, 520px);
|
||||
}
|
||||
|
||||
.field--slider {
|
||||
@@ -1548,6 +1598,13 @@ progress.progress::-moz-progress-bar {
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||||
border: 1px solid rgba(148, 163, 184, 0.18);
|
||||
}
|
||||
|
||||
.voice-preview textarea {
|
||||
border-radius: 14px;
|
||||
border: 1px solid rgba(148, 163, 184, 0.25);
|
||||
background: rgba(11, 18, 34, 0.85);
|
||||
min-height: 140px;
|
||||
}
|
||||
|
||||
.voice-status {
|
||||
min-height: 1.2rem;
|
||||
font-size: 0.9rem;
|
||||
|
||||
@@ -7,130 +7,138 @@
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||||
<div class="card__title">Prepare audiobook</div>
|
||||
<p class="card__subtitle">Review the detected chapters, choose which ones to render, and optionally override the voice per chapter before sending the job to the queue.</p>
|
||||
|
||||
{% set analysis = pending.speaker_analysis or {} %}
|
||||
{% set analysis_speakers = analysis.get('speakers', {}) %}
|
||||
{% set show_analysis_prompt = pending.speaker_mode == 'multi' and not pending.analysis_requested %}
|
||||
{% set has_metadata = pending.metadata_tags %}
|
||||
<div class="prepare-summary">
|
||||
<dl>
|
||||
<div>
|
||||
<dt>Source</dt>
|
||||
<dd>{{ pending.original_filename }}</dd>
|
||||
<div class="prepare-summary__stats">
|
||||
<dl>
|
||||
<div>
|
||||
<dt>Source</dt>
|
||||
<dd>{{ pending.original_filename }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Language</dt>
|
||||
<dd>{{ options.languages.get(pending.language, pending.language|upper) }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Default voice</dt>
|
||||
<dd>{% if pending.voice_profile %}Profile · {{ pending.voice_profile }}{% else %}{{ pending.voice }}{% endif %}</dd>
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||||
</div>
|
||||
<div>
|
||||
<dt>Total chapters</dt>
|
||||
<dd>{{ pending.chapters|length }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Characters</dt>
|
||||
<dd>{{ '{:,}'.format(pending.total_characters|default(0)) }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Chapter intro delay</dt>
|
||||
<dd>{{ '%.1f'|format(pending.chapter_intro_delay) }} seconds</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Chunk granularity</dt>
|
||||
<dd>{{ pending.chunk_level|replace('_', ' ')|title }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Speaker mode</dt>
|
||||
<dd>{{ pending.speaker_mode|replace('_', ' ')|title }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Speaker analysis threshold</dt>
|
||||
<dd>{{ pending.speaker_analysis_threshold }} {{ 'mention' if pending.speaker_analysis_threshold == 1 else 'mentions' }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>EPUB 3 package</dt>
|
||||
<dd>{% if pending.generate_epub3 %}Enabled{% else %}Disabled{% endif %}</dd>
|
||||
</div>
|
||||
</dl>
|
||||
</div>
|
||||
{% if analysis_speakers or show_analysis_prompt or has_metadata %}
|
||||
<div class="prepare-summary__insights">
|
||||
{% if analysis_speakers %}
|
||||
{% set active = namespace(items=[]) %}
|
||||
{% for sid, payload in analysis_speakers.items() %}
|
||||
{% if sid != 'narrator' and not payload.get('suppressed') %}
|
||||
{% set _ = active.items.append(payload) %}
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
<div class="prepare-analysis">
|
||||
<h2>Detected speakers</h2>
|
||||
{% if active.items %}
|
||||
<ul>
|
||||
{% for speaker in active.items|sort(attribute='label') %}
|
||||
<li><strong>{{ speaker.label }}</strong> · {{ speaker.count }} lines · confidence {{ speaker.confidence|title }}</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
{% else %}
|
||||
<p>No additional speakers met the threshold yet. All dialogue will use the narrator voice.</p>
|
||||
{% endif %}
|
||||
</div>
|
||||
<div>
|
||||
<dt>Language</dt>
|
||||
<dd>{{ options.languages.get(pending.language, pending.language|upper) }}</dd>
|
||||
{% elif show_analysis_prompt %}
|
||||
<div class="prepare-analysis">
|
||||
<h2>Detected speakers</h2>
|
||||
<p>Press <strong>Analyze speakers</strong> after selecting chapters to discover recurring voices.</p>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Default voice</dt>
|
||||
<dd>{% if pending.voice_profile %}Profile · {{ pending.voice_profile }}{% else %}{{ pending.voice }}{% endif %}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Total chapters</dt>
|
||||
<dd>{{ pending.chapters|length }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Characters</dt>
|
||||
<dd>{{ pending.total_characters|default(0) }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Chapter intro delay</dt>
|
||||
<dd>{{ '%.1f'|format(pending.chapter_intro_delay) }} seconds</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Chunk granularity</dt>
|
||||
<dd>{{ pending.chunk_level|replace('_', ' ')|title }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Speaker mode</dt>
|
||||
<dd>{{ pending.speaker_mode|replace('_', ' ')|title }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>Speaker analysis threshold</dt>
|
||||
<dd>{{ pending.speaker_analysis_threshold }} {{ 'mention' if pending.speaker_analysis_threshold == 1 else 'mentions' }}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>EPUB 3 package</dt>
|
||||
<dd>{% if pending.generate_epub3 %}Enabled{% else %}Disabled{% endif %}</dd>
|
||||
</div>
|
||||
</dl>
|
||||
{% set analysis = pending.speaker_analysis or {} %}
|
||||
{% set analysis_speakers = analysis.get('speakers', {}) %}
|
||||
{% if analysis_speakers %}
|
||||
{% set active = namespace(items=[]) %}
|
||||
{% for sid, payload in analysis_speakers.items() %}
|
||||
{% if sid != 'narrator' and not payload.get('suppressed') %}
|
||||
{% set _ = active.items.append(payload) %}
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
<div class="prepare-analysis">
|
||||
<h2>Detected speakers</h2>
|
||||
{% if active.items %}
|
||||
<ul>
|
||||
{% for speaker in active.items|sort(attribute='label') %}
|
||||
<li><strong>{{ speaker.label }}</strong> · {{ speaker.count }} lines · confidence {{ speaker.confidence|title }}</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
{% else %}
|
||||
<p>No additional speakers met the threshold yet. All dialogue will use the narrator voice.</p>
|
||||
{% if has_metadata %}
|
||||
<div class="prepare-metadata">
|
||||
<h2>Metadata</h2>
|
||||
<ul>
|
||||
{% for key, value in pending.metadata_tags.items() %}
|
||||
<li><strong>{{ key|replace('_', ' ')|title }}:</strong> {{ value }}</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
{% elif pending.speaker_mode == 'multi' and not pending.analysis_requested %}
|
||||
<div class="prepare-analysis">
|
||||
<h2>Detected speakers</h2>
|
||||
<p>Press <strong>Analyze speakers</strong> after selecting chapters to discover recurring voices.</p>
|
||||
</div>
|
||||
{% endif %}
|
||||
{% set roster = pending.speakers or {} %}
|
||||
{% if roster %}
|
||||
{% set preview_template = options.speaker_pronunciation_sentence or "This is {{name}} speaking." %}
|
||||
<div class="prepare-speakers">
|
||||
<h2>Speaker pronunciation guide</h2>
|
||||
<p class="hint">Add a phonetic spelling (IPA or plain text) so pronunciations sound right. Leave blank to use the written label.</p>
|
||||
<ul class="speaker-list">
|
||||
{% for speaker_id, speaker in roster.items() %}
|
||||
{% set spoken_name = speaker.pronunciation or speaker.label %}
|
||||
{% set preview_text = preview_template | replace("{{name}}", spoken_name) %}
|
||||
<li class="speaker-list__item">
|
||||
<div class="speaker-list__header">
|
||||
<span class="speaker-list__name">{{ speaker.label }}</span>
|
||||
<button type="button"
|
||||
class="icon-button speaker-list__preview"
|
||||
data-role="speaker-preview"
|
||||
data-speaker-id="{{ speaker_id }}"
|
||||
data-preview-text="{{ preview_text|e }}"
|
||||
data-language="{{ pending.language }}"
|
||||
data-voice="{{ speaker.resolved_voice or speaker.voice_formula or speaker.voice or pending.voice }}"
|
||||
data-speed="{{ '%.2f'|format(pending.speed) }}"
|
||||
data-use-gpu="{{ 'true' if pending.use_gpu else 'false' }}"
|
||||
aria-label="Preview pronunciation for {{ speaker.label }}"
|
||||
title="Preview pronunciation">
|
||||
🔊
|
||||
</button>
|
||||
</div>
|
||||
<label class="speaker-list__field" for="speaker-{{ speaker_id }}-pronunciation">
|
||||
<span>Pronunciation</span>
|
||||
<input type="text"
|
||||
id="speaker-{{ speaker_id }}-pronunciation"
|
||||
name="speaker-{{ speaker_id }}-pronunciation"
|
||||
value="{{ speaker.pronunciation or '' }}"
|
||||
placeholder="{{ speaker.label }}">
|
||||
</label>
|
||||
{% if speaker.get('analysis_count') %}
|
||||
<p class="hint speaker-list__stats">{{ speaker.analysis_count }} detected lines · confidence {{ speaker.analysis_confidence|default('low')|title }}</p>
|
||||
{% endif %}
|
||||
</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
{% endif %}
|
||||
{% if pending.metadata_tags %}
|
||||
<div class="prepare-metadata">
|
||||
<h2>Metadata</h2>
|
||||
<ul>
|
||||
{% for key, value in pending.metadata_tags.items() %}
|
||||
<li><strong>{{ key|replace('_', ' ')|title }}:</strong> {{ value }}</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
{% set roster = pending.speakers or {} %}
|
||||
{% if roster %}
|
||||
{% set preview_template = options.speaker_pronunciation_sentence or "This is {{name}} speaking." %}
|
||||
<div class="prepare-speakers">
|
||||
<h2>Speaker pronunciation guide</h2>
|
||||
<p class="hint">Add a phonetic spelling (IPA or plain text) so pronunciations sound right. Leave blank to use the written label.</p>
|
||||
<ul class="speaker-list">
|
||||
{% for speaker_id, speaker in roster.items() %}
|
||||
{% set spoken_name = speaker.pronunciation or speaker.label %}
|
||||
{% set preview_text = preview_template | replace("{{name}}", spoken_name) %}
|
||||
<li class="speaker-list__item">
|
||||
<div class="speaker-list__header">
|
||||
<span class="speaker-list__name">{{ speaker.label }}</span>
|
||||
<button type="button"
|
||||
class="icon-button speaker-list__preview"
|
||||
data-role="speaker-preview"
|
||||
data-speaker-id="{{ speaker_id }}"
|
||||
data-preview-text="{{ preview_text|e }}"
|
||||
data-language="{{ pending.language }}"
|
||||
data-voice="{{ speaker.resolved_voice or speaker.voice_formula or speaker.voice or pending.voice }}"
|
||||
data-speed="{{ '%.2f'|format(pending.speed) }}"
|
||||
data-use-gpu="{{ 'true' if pending.use_gpu else 'false' }}"
|
||||
aria-label="Preview pronunciation for {{ speaker.label }}"
|
||||
title="Preview pronunciation">
|
||||
🔊
|
||||
</button>
|
||||
</div>
|
||||
<label class="speaker-list__field" for="speaker-{{ speaker_id }}-pronunciation">
|
||||
<span>Pronunciation</span>
|
||||
<input type="text"
|
||||
id="speaker-{{ speaker_id }}-pronunciation"
|
||||
name="speaker-{{ speaker_id }}-pronunciation"
|
||||
value="{{ speaker.pronunciation or '' }}"
|
||||
placeholder="{{ speaker.label }}">
|
||||
</label>
|
||||
{% if speaker.get('analysis_count') %}
|
||||
<p class="hint speaker-list__stats">{{ speaker.analysis_count }} detected lines · confidence {{ speaker.analysis_confidence|default('low')|title }}</p>
|
||||
{% endif %}
|
||||
</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
{% endif %}
|
||||
|
||||
{% if error %}
|
||||
<div class="alert alert--error">{{ error }}</div>
|
||||
@@ -160,7 +168,7 @@
|
||||
</label>
|
||||
</div>
|
||||
<div class="chapter-card__metrics">
|
||||
{{ chapter.characters }} characters
|
||||
{{ '{:,}'.format(chapter.characters) }} characters
|
||||
</div>
|
||||
</header>
|
||||
<div class="chapter-card__body">
|
||||
|
||||
@@ -0,0 +1,13 @@
|
||||
import importlib
|
||||
import sys
|
||||
|
||||
# Ensure real optional dependencies are imported before tests that install stubs
|
||||
# so that available packages (like ebooklib, bs4) aren't replaced with dummy modules.
|
||||
for module_name in ("ebooklib", "bs4"):
|
||||
if module_name not in sys.modules:
|
||||
try:
|
||||
importlib.import_module(module_name)
|
||||
except Exception:
|
||||
# On environments without the optional dependency, downstream tests
|
||||
# will install lightweight stubs as needed.
|
||||
pass
|
||||
@@ -0,0 +1,44 @@
|
||||
from abogen.speaker_analysis import analyze_speakers
|
||||
|
||||
|
||||
def _chapters():
|
||||
return [
|
||||
{
|
||||
"id": "0001",
|
||||
"index": 0,
|
||||
"title": "Test",
|
||||
"text": "",
|
||||
"enabled": True,
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
def _chunk(text: str, idx: int) -> dict:
|
||||
return {
|
||||
"id": f"chunk-{idx}",
|
||||
"chapter_index": 0,
|
||||
"chunk_index": idx,
|
||||
"text": text,
|
||||
}
|
||||
|
||||
|
||||
def test_analyze_speakers_infers_gender_from_pronouns():
|
||||
chunks = [
|
||||
_chunk("\"Greetings,\" said John. He adjusted his hat as he smiled.", 0),
|
||||
_chunk("\"Hello,\" said Mary. She straightened her dress as she introduced herself.", 1),
|
||||
_chunk("\"Nice to meet you,\" said Alex.", 2),
|
||||
]
|
||||
|
||||
analysis = analyze_speakers(_chapters(), chunks, threshold=1, max_speakers=0)
|
||||
|
||||
john = analysis.speakers.get("john")
|
||||
mary = analysis.speakers.get("mary")
|
||||
alex = analysis.speakers.get("alex")
|
||||
|
||||
assert john is not None
|
||||
assert mary is not None
|
||||
assert alex is not None
|
||||
|
||||
assert john.gender == "male"
|
||||
assert mary.gender == "female"
|
||||
assert alex.gender == "unknown"
|
||||
@@ -0,0 +1,27 @@
|
||||
from pathlib import Path
|
||||
|
||||
from abogen.text_extractor import extract_from_path
|
||||
from abogen.utils import calculate_text_length
|
||||
|
||||
|
||||
ASSET = Path("test_assets/alexandre-dumas_the-count-of-monte-cristo_chapman-and-hall.epub")
|
||||
|
||||
|
||||
def test_epub_character_counts_align_with_calculated_total():
|
||||
result = extract_from_path(ASSET)
|
||||
|
||||
combined_total = calculate_text_length(result.combined_text)
|
||||
chapter_total = sum(chapter.characters for chapter in result.chapters)
|
||||
|
||||
assert result.total_characters == combined_total == chapter_total
|
||||
|
||||
|
||||
def test_epub_metadata_composer_matches_artist():
|
||||
result = extract_from_path(ASSET)
|
||||
|
||||
composer = result.metadata.get("composer") or result.metadata.get("COMPOSER")
|
||||
artist = result.metadata.get("artist") or result.metadata.get("ARTIST")
|
||||
|
||||
assert composer
|
||||
assert composer == artist
|
||||
assert composer != "Narrator"
|
||||
Reference in New Issue
Block a user