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PaddleSpeech/paddlespeech/s2t/models/whisper/utils.py

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2.8 KiB

# MIT License, Copyright (c) 2022 OpenAI.
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Modified from OpenAI Whisper 2022 (https://github.com/openai/whisper/whisper/utils.py)
import zlib
from typing import Iterator
from typing import TextIO
def exact_div(x, y):
assert x % y == 0
return x // y
def str2bool(string):
str2val = {"True": True, "False": False}
if string in str2val:
return str2val[string]
else:
raise ValueError(f"Expected one of {set(str2val.keys())}, got {string}")
def optional_int(string):
return None if string == "None" else int(string)
def optional_float(string):
return None if string == "None" else float(string)
def compression_ratio(text) -> float:
return len(text) / len(zlib.compress(text.encode("utf-8")))
def format_timestamp(seconds: float,
always_include_hours: bool=False,
decimal_marker: str='.'):
assert seconds >= 0, "non-negative timestamp expected"
milliseconds = round(seconds * 1000.0)
hours = milliseconds // 3_600_000
milliseconds -= hours * 3_600_000
minutes = milliseconds // 60_000
milliseconds -= minutes * 60_000
seconds = milliseconds // 1_000
milliseconds -= seconds * 1_000
hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else ""
return f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}"
def write_txt(transcript: Iterator[dict], file: TextIO):
for segment in transcript:
print(segment['text'].strip(), file=file, flush=True)
def write_vtt(transcript: Iterator[dict], file: TextIO):
print("WEBVTT\n", file=file)
for segment in transcript:
print(
f"{format_timestamp(segment['start'])} --> {format_timestamp(segment['end'])}\n"
f"{segment['text'].strip().replace('-->', '->')}\n",
file=file,
flush=True, )
def write_srt(transcript: Iterator[dict], file: TextIO):
"""
Write a transcript to a file in SRT format.
Example usage:
from pathlib import Path
from whisper.utils import write_srt
result = transcribe(model, audio_path, temperature=temperature, **args)
# save SRT
audio_basename = Path(audio_path).stem
with open(Path(output_dir) / (audio_basename + ".srt"), "w", encoding="utf-8") as srt:
write_srt(result["segments"], file=srt)
"""
for i, segment in enumerate(transcript, start=1):
# write srt lines
print(
f"{i}\n"
f"{format_timestamp(segment['start'], always_include_hours=True, decimal_marker=',')} --> "
f"{format_timestamp(segment['end'], always_include_hours=True, decimal_marker=',')}\n"
f"{segment['text'].strip().replace('-->', '->')}\n",
file=file,
flush=True, )