from __future__ import annotations import re from typing import TYPE_CHECKING from pydantic import BaseModel from faster_whisper_server.config import config if TYPE_CHECKING: from collections.abc import Iterable import faster_whisper.transcribe class Word(BaseModel): start: float end: float word: str probability: float @classmethod def from_segments(cls, segments: Iterable[Segment]) -> list[Word]: words: list[Word] = [] for segment in segments: assert segment.words is not None words.extend(segment.words) return words def offset(self, seconds: float) -> None: self.start += seconds self.end += seconds @classmethod def common_prefix(cls, a: list[Word], b: list[Word]) -> list[Word]: i = 0 while i < len(a) and i < len(b) and canonicalize_word(a[i].word) == canonicalize_word(b[i].word): i += 1 return a[:i] class Segment(BaseModel): id: int seek: int start: float end: float text: str tokens: list[int] temperature: float avg_logprob: float compression_ratio: float no_speech_prob: float words: list[Word] | None @classmethod def from_faster_whisper_segments(cls, segments: Iterable[faster_whisper.transcribe.Segment]) -> Iterable[Segment]: for segment in segments: yield cls( id=segment.id, seek=segment.seek, start=segment.start, end=segment.end, text=segment.text, tokens=segment.tokens, temperature=segment.temperature, avg_logprob=segment.avg_logprob, compression_ratio=segment.compression_ratio, no_speech_prob=segment.no_speech_prob, words=[ Word( start=word.start, end=word.end, word=word.word, probability=word.probability, ) for word in segment.words ] if segment.words is not None else None, ) class Transcription: def __init__(self, words: list[Word] = []) -> None: self.words: list[Word] = [] self.extend(words) @property def text(self) -> str: return " ".join(word.word for word in self.words).strip() @property def start(self) -> float: return self.words[0].start if len(self.words) > 0 else 0.0 @property def end(self) -> float: return self.words[-1].end if len(self.words) > 0 else 0.0 @property def duration(self) -> float: return self.end - self.start def after(self, seconds: float) -> Transcription: return Transcription(words=[word for word in self.words if word.start > seconds]) def extend(self, words: list[Word]) -> None: self._ensure_no_word_overlap(words) self.words.extend(words) def _ensure_no_word_overlap(self, words: list[Word]) -> None: if len(self.words) > 0 and len(words) > 0: if words[0].start + config.word_timestamp_error_margin <= self.words[-1].end: raise ValueError( f"Words overlap: {self.words[-1]} and {words[0]}. Error margin: {config.word_timestamp_error_margin}" # noqa: E501 ) for i in range(1, len(words)): if words[i].start + config.word_timestamp_error_margin <= words[i - 1].end: raise ValueError(f"Words overlap: {words[i - 1]} and {words[i]}. All words: {words}") def is_eos(text: str) -> bool: if text.endswith("..."): return False return any(text.endswith(punctuation_symbol) for punctuation_symbol in ".?!") def test_is_eos() -> None: assert not is_eos("Hello") assert not is_eos("Hello...") assert is_eos("Hello.") assert is_eos("Hello!") assert is_eos("Hello?") assert not is_eos("Hello. Yo") assert not is_eos("Hello. Yo...") assert is_eos("Hello. Yo.") def to_full_sentences(words: list[Word]) -> list[list[Word]]: sentences: list[list[Word]] = [[]] for word in words: sentences[-1].append(word) if is_eos(word.word): sentences.append([]) if len(sentences[-1]) == 0 or not is_eos(sentences[-1][-1].word): sentences.pop() return sentences def tests_to_full_sentences() -> None: def word(text: str) -> Word: return Word(word=text, start=0.0, end=0.0, probability=0.0) assert to_full_sentences([]) == [] assert to_full_sentences([word(text="Hello")]) == [] assert to_full_sentences([word(text="Hello..."), word(" world")]) == [] assert to_full_sentences([word(text="Hello..."), word(" world.")]) == [[word("Hello..."), word(" world.")]] assert to_full_sentences([word(text="Hello..."), word(" world."), word(" How")]) == [ [word("Hello..."), word(" world.")], ] def word_to_text(words: list[Word]) -> str: return "".join(word.word for word in words) def words_to_text_w_ts(words: list[Word]) -> str: return "".join(f"{word.word}({word.start:.2f}-{word.end:.2f})" for word in words) def segments_to_text(segments: Iterable[Segment]) -> str: return "".join(segment.text for segment in segments).strip() def canonicalize_word(text: str) -> str: text = text.lower() # Remove non-alphabetic characters using regular expression text = re.sub(r"[^a-z]", "", text) return text.lower().strip().strip(".,?!") def test_canonicalize_word() -> None: assert canonicalize_word("ABC") == "abc" assert canonicalize_word("...ABC?") == "abc" assert canonicalize_word("... AbC ...") == "abc" def common_prefix(a: list[Word], b: list[Word]) -> list[Word]: i = 0 while i < len(a) and i < len(b) and canonicalize_word(a[i].word) == canonicalize_word(b[i].word): i += 1 return a[:i] def test_common_prefix() -> None: def word(text: str) -> Word: return Word(word=text, start=0.0, end=0.0, probability=0.0) a = [word("a"), word("b"), word("c")] b = [word("a"), word("b"), word("c")] assert common_prefix(a, b) == [word("a"), word("b"), word("c")] a = [word("a"), word("b"), word("c")] b = [word("a"), word("b"), word("d")] assert common_prefix(a, b) == [word("a"), word("b")] a = [word("a"), word("b"), word("c")] b = [word("a")] assert common_prefix(a, b) == [word("a")] a = [word("a")] b = [word("a"), word("b"), word("c")] assert common_prefix(a, b) == [word("a")] a = [word("a")] b = [] assert common_prefix(a, b) == [] a = [] b = [word("a")] assert common_prefix(a, b) == [] a = [word("a"), word("b"), word("c")] b = [word("b"), word("c")] assert common_prefix(a, b) == [] def test_common_prefix_and_canonicalization() -> None: def word(text: str) -> Word: return Word(word=text, start=0.0, end=0.0, probability=0.0) a = [word("A...")] b = [word("a?"), word("b"), word("c")] assert common_prefix(a, b) == [word("A...")] a = [word("A..."), word("B?"), word("C,")] b = [word("a??"), word(" b"), word(" ,c")] assert common_prefix(a, b) == [word("A..."), word("B?"), word("C,")]