Steffen Albrecht
425 lines
14 KiB
Python
425 lines
14 KiB
Python
import json
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import time
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from typing import Union
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ALPHABET = [*"abcdefghijklmnopqrstuvwxyz"]
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# List of known hallucinations - adapted from:
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# https://github.com/openai/whisper/discussions/928
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WHISPER_HALLUCINATIONS={
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"en": [
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" www.mooji.org",
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],
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"nl": [
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" Ondertitels ingediend door de Amara.org gemeenschap",
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" Ondertiteld door de Amara.org gemeenschap",
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" Ondertiteling door de Amara.org gemeenschap"
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],
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"de": [
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" Untertitelung aufgrund der Amara.org-Community"
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" Untertitelung im Auftrag des ZDF für funk, 2016",
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" Untertitelung im Auftrag des ZDF f\u00fcr funk, 2016",
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" Untertitel im Auftrag des ZDF für funk, 2017",
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" Untertitel im Auftrag des ZDF f\u00fcr funk, 2017",
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" Untertitel im Auftrag des ZDF für funk, 2018",
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" Untertitel von Stephanie Geiges",
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" Untertitel der Amara.org-Community",
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" Untertitel im Auftrag des ZDF, 2017",
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" Untertitel im Auftrag des ZDF, 2018",
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" Untertitel im Auftrag des ZDF, 2019",
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" Untertitel im Auftrag des ZDF, 2020",
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" Untertitel im Auftrag des ZDF, 2021",
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" Untertitelung im Auftrag des ZDF, 2021",
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" Copyright WDR 2021",
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" Copyright WDR 2020",
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" Copyright WDR 2019",
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" SWR 2021",
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" SWR 2020",
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],
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"fr": [
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" Sous-titres réalisés para la communauté d'Amara.org",
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" Sous-titres réalisés par la communauté d'Amara.org",
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" Sous-titres fait par Sous-titres par Amara.org",
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" Sous-titres réalisés par les SousTitres d'Amara.org",
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" Sous-titres par Amara.org",
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" Sous-titres par la communauté d'Amara.org",
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" Sous-titres réalisés pour la communauté d'Amara.org",
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" Sous-titres réalisés par la communauté de l'Amara.org",
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" Sous-Titres faits par la communauté d'Amara.org",
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" Sous-titres par l'Amara.org",
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" Sous-titres fait par la communauté d'Amara.org"
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" Sous-titrage ST' 501",
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" Sous-titrage ST'501",
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" Cliquez-vous sur les sous-titres et abonnez-vous à la chaîne d'Amara.org",
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" ❤️ par SousTitreur.com",
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],
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"it": [
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" Sottotitoli creati dalla comunità Amara.org",
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" Sottotitoli di Sottotitoli di Amara.org",
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" Sottotitoli e revisione al canale di Amara.org",
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" Sottotitoli e revisione a cura di Amara.org",
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" Sottotitoli e revisione a cura di QTSS",
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" Sottotitoli e revisione a cura di QTSS.",
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" Sottotitoli a cura di QTSS",
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],
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"es": [
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" Subtítulos realizados por la comunidad de Amara.org",
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" Subtitulado por la comunidad de Amara.org",
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" Subtítulos por la comunidad de Amara.org",
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" Subtítulos creados por la comunidad de Amara.org",
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" Subtítulos en español de Amara.org",
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" Subtítulos hechos por la comunidad de Amara.org",
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" Subtitulos por la comunidad de Amara.org"
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" Más información www.alimmenta.com",
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" www.mooji.org",
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],
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"gl": [
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" Subtítulos realizados por la comunidad de Amara.org"
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],
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"pt": [
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" Legendas pela comunidade Amara.org",
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" Legendas pela comunidade de Amara.org",
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" Legendas pela comunidade do Amara.org",
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" Legendas pela comunidade das Amara.org",
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" Transcrição e Legendas pela comunidade de Amara.org"
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],
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"la": [
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" Sottotitoli creati dalla comunità Amara.org",
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" Sous-titres réalisés para la communauté d'Amara.org"
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],
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"ln": [
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" Sous-titres réalisés para la communauté d'Amara.org"
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],
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"pl": [
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" Napisy stworzone przez społeczność Amara.org",
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" Napisy wykonane przez społeczność Amara.org",
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" Zdjęcia i napisy stworzone przez społeczność Amara.org",
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" napisy stworzone przez społeczność Amara.org",
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" Tłumaczenie i napisy stworzone przez społeczność Amara.org",
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" Napisy stworzone przez społeczności Amara.org",
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" Tłumaczenie stworzone przez społeczność Amara.org",
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" Napisy robione przez społeczność Amara.org"
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" www.multi-moto.eu",
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],
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"ru": [
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" Редактор субтитров А.Синецкая Корректор А.Егорова"
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],
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"tr": [
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" Yorumlarınızıza abone olmayı unutmayın.",
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],
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"su": [
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" Sottotitoli creati dalla comunità Amara.org"
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],
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"zh": [
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"字幕由Amara.org社区提供",
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"小編字幕由Amara.org社區提供"
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]
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}
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class Transcript:
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"""
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Class for storing transcript data, including speaker information and text segments,
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and exporting it to various file formats such as JSON, HTML, and LaTeX.
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"""
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def __init__(self, transcript: dict) -> None:
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"""
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Initializes the Transcript object with the given transcript data.
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Args:
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transcript (dict): A dictionary containing the formatted transcript string.
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Keys should correspond to segment IDs, and values should
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contain speaker and segment information.
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"""
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self.transcript = transcript
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self._remove_hallucinations()
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self.speakers = self._extract_speakers()
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self.segments = self._extract_segments()
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self.annotation = {}
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def annotate(self, *args, **kwargs) -> dict:
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"""
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Annotates the transcript to associate specific names with speakers.
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Args:
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args (list): List of speaker names. These will be mapped sequentially to the speakers.
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kwargs (dict): Dictionary with speaker names as keys and list of segments as values.
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Returns:
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dict: Dictionary with speaker names as keys and list of segments as values.
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Raises:
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ValueError: If the number of speaker names does not match the number
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of speakers, or if an unknown speaker is found.
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"""
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annotations = {}
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if args and len(args) != len(self.speakers):
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raise ValueError("Number of speaker names does not match number of speakers")
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if args:
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for arg, speaker in zip(args, sorted(self.speakers)):
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annotations[speaker] = arg
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invalid_speakers = set(kwargs.keys()) - set(self.speakers)
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if invalid_speakers:
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raise ValueError(f"These keys are not speakers: {', '.join(invalid_speakers)}")
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annotations.update({key: kwargs[key] for key in self.speakers if key in kwargs})
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self.annotation = annotations
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return self
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def _remove_hallucinations(self) -> None:
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segments_to_drop=[]
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for id in self.transcript:
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for language, snippets in WHISPER_HALLUCINATIONS.items():
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for snippet in snippets:
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self.transcript[id]['text']=self.transcript[id]['text'].replace(snippet,'')
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if self.transcript[id]['text'] == '': segments_to_drop.append(id)
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for id in segments_to_drop:
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del self.transcript[id]
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def _extract_speakers(self) -> list:
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"""
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Extracts the unique speaker names from the transcript.
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Returns:
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list: List of unique speaker names in the transcript.
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"""
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return list(set([self.transcript[id]["speakers"] for id in self.transcript]))
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def _extract_segments(self) -> list:
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"""
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Extracts all the text segments from the transcript.
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Returns:
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list: List of segments, where each segment is represented
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by the starting and ending times.
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"""
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return [self.transcript[id]["segments"] for id in self.transcript]
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def __str__(self) -> str:
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"""
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Converts the transcript to a string representation.
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Returns:
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str: String representation of the transcript, including speaker names and
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time stamps for each segment.
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"""
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fstring = ""
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for _id in self.transcript:
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seq = self.transcript[_id]
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if self.annotation:
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speaker = self.annotation[seq["speakers"]]
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else:
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speaker = seq["speakers"]
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segm = seq["segments"]
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sseg = time.strftime("%H:%M:%S",time.gmtime(segm[0]))
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eseg = time.strftime("%H:%M:%S",time.gmtime(segm[1]))
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fstring += f"{speaker} ({sseg} ; {eseg}):\t{seq['text']}\n"
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return fstring
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def __repr__(self) -> str:
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"""Return a string representation of the Transcript object.
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Returns:
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str: A string that provides an informative description of the object.
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"""
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return f"Transcript(speakers = {self.speakers},"\
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f"segments = {self.segments}, annotation = {self.annotation})"
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def get_dict(self) -> dict:
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"""
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Get transcript as dict
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:return: transcript as dict
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:rtype: dict
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"""
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return self.transcript
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def get_json(self, *args, use_annotation : bool = True, **kwargs) -> str:
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"""
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Get transcript as json string
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:return: transcript as json string
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:rtype: str
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"""
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if "indent" not in kwargs:
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kwargs["indent"] = 3
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if use_annotation and self.annotation:
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for _id in self.transcript:
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seq = self.transcript[_id]
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seq["speakers"] = self.annotation[seq["speakers"]]
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return json.dumps(self.transcript, *args, **kwargs)
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def get_html(self) -> str:
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"""
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Get transcript as html string
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:return: transcript as html string
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:rtype: str
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"""
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html = "<p>" + self.__str__().replace("\n", "<br>") + "</p>"
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html = "<html><body>" + html + "</body></html>"
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html = html.replace("\t", " ")
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return html
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def get_md(self) -> str:
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"""Get transcript as Markdown string, using HTML formatting.
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Returns:
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str: Transcript as a Markdown string.
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"""
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return self.get_html()
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def get_tex(self) -> str:
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"""Get transcript as LaTeX string. If no annotations are present, the speakers will
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be annotated with the first letters of the alphabet.
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Returns:
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str: Transcript as LaTeX string.
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"""
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if not self.annotation:
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self.annotate(*ALPHABET[:len(self.speakers)])
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fstring ="\\begin{drama}"
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for speaker in self.speakers:
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fstring += "\n\t\\Character{"+ str(self.annotation[speaker]) + "}" \
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"{"+ str(self.annotation[speaker]) + "}"
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for id in self.transcript:
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seq = self.transcript[id]
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speaker = self.annotation[seq["speakers"]]
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fstring += f"\n\\{speaker}speaks:\n{seq['text']}"
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fstring += "\n\\end{drama}"
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return fstring
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def to_json(self,path, *args, **kwargs) -> None:
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"""Save transcript as json file
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Args:
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path (str): path to save file
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"""
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with open(path, "w") as f:
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json.dump(self.transcript, f, *args, **kwargs)
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def to_txt(self, path: str) -> None:
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"""Save transcript as a LaTeX file (placeholder function, implementation needed).
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Args:
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path (str): Path to save the LaTeX file.
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"""
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with open(path, "w") as f:
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f.write(self.__str__())
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def to_md(self, path: str) -> None:
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"""Get transcript as Markdown string, using HTML formatting.
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Returns:
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str: Transcript as a Markdown string.
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"""
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return self.to_html(path)
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def to_html(self, path: str) -> None:
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"""
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Save transcript as html file
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:param path: path to save file
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:type path: str
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"""
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with open(path, "w") as file:
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file.write(self.get_html())
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def to_tex(self, path: str) -> None:
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"""Save transcript as a LaTeX file (placeholder function, implementation needed).
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Args:
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path (str): Path to save the LaTeX file.
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"""
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pass
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def to_pdf(self, path: str) -> None:
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"""Save transcript as a PDF file (placeholder function, implementation needed).
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Args:
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path (str): Path to save the PDF file.
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"""
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pass
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def save(self, path: str, *args, **kwargs) -> None:
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"""Save transcript to file with the given path and file format.
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This method can save the transcript in various formats including JSON, TXT,
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MD, HTML, TEX, and PDF. The file format is determined by the extension of
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the path.
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Args:
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path (str): Path to save the file, including the desired file extension.
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*args: Additional positional arguments to be passed to the specific save methods.
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**kwargs: Additional keyword arguments to be passed to the specific save methods.
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Raises:
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ValueError: If the file format specified in the path is unknown.
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"""
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if path.endswith(".json"):
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self.to_json(path, *args, **kwargs)
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elif path.endswith(".txt"):
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self.to_txt(path, *args, **kwargs)
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elif path.endswith(".md"):
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self.to_md(path, *args, **kwargs)
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elif path.endswith(".html"):
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self.to_html(path, *args, **kwargs)
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elif path.endswith(".tex"):
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self.to_tex(path, *args, **kwargs)
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elif path.endswith(".pdf"):
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self.to_pdf(path, *args, **kwargs)
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else:
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raise ValueError("Unknown file format")
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@classmethod
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def from_json(cls, json: Union[dict, str]) -> "Transcript":
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"""Load transcript from json file
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Args:
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path (str): path to json file
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Returns:
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Transcript: Transcript object
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"""
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if isinstance(json, dict):
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return cls(json)
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else:
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try:
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transcript = json.loads(json)
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except:
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with open(json, "r") as f:
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transcript = json.load(f)
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return cls(transcript)
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