Fedir Zadniprovskyi
feat: handle srt and vtt response formats
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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 srt_format_timestamp(ts: float) -> str:
hours = ts // 3600
minutes = (ts % 3600) // 60
seconds = ts % 60
milliseconds = (ts * 1000) % 1000
return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d},{int(milliseconds):03d}"
def test_srt_format_timestamp() -> None:
assert srt_format_timestamp(0.0) == "00:00:00,000"
assert srt_format_timestamp(1.0) == "00:00:01,000"
assert srt_format_timestamp(1.234) == "00:00:01,234"
assert srt_format_timestamp(60.0) == "00:01:00,000"
assert srt_format_timestamp(61.0) == "00:01:01,000"
assert srt_format_timestamp(61.234) == "00:01:01,234"
assert srt_format_timestamp(3600.0) == "01:00:00,000"
assert srt_format_timestamp(3601.0) == "01:00:01,000"
assert srt_format_timestamp(3601.234) == "01:00:01,234"
assert srt_format_timestamp(23423.4234) == "06:30:23,423"
def vtt_format_timestamp(ts: float) -> str:
hours = ts // 3600
minutes = (ts % 3600) // 60
seconds = ts % 60
milliseconds = (ts * 1000) % 1000
return f"{int(hours):02d}:{int(minutes):02d}:{int(seconds):02d}.{int(milliseconds):03d}"
def test_vtt_format_timestamp() -> None:
assert vtt_format_timestamp(0.0) == "00:00:00.000"
assert vtt_format_timestamp(1.0) == "00:00:01.000"
assert vtt_format_timestamp(1.234) == "00:00:01.234"
assert vtt_format_timestamp(60.0) == "00:01:00.000"
assert vtt_format_timestamp(61.0) == "00:01:01.000"
assert vtt_format_timestamp(61.234) == "00:01:01.234"
assert vtt_format_timestamp(3600.0) == "01:00:00.000"
assert vtt_format_timestamp(3601.0) == "01:00:01.000"
assert vtt_format_timestamp(3601.234) == "01:00:01.234"
assert vtt_format_timestamp(23423.4234) == "06:30:23.423"
def segments_to_vtt(segment: Segment, i: int) -> str:
start = segment.start if i > 0 else 0.0
result = f"{vtt_format_timestamp(start)} --> {vtt_format_timestamp(segment.end)}\n{segment.text}\n\n"
if i == 0:
return f"WEBVTT\n\n{result}"
else:
return result
def segments_to_srt(segment: Segment, i: int) -> str:
return f"{i + 1}\n{srt_format_timestamp(segment.start)} --> {srt_format_timestamp(segment.end)}\n{segment.text}\n\n"
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,")]