code: def get_ctm_line(
      source: str,
      channel: int,
      start_time: float,
      duration: float,
      token: str,
      conf: float,
      type_of_token: str,
      speaker: str,
      NA_token: str = "NA",
      UNK: str = "unknown",
      default_channel: str = "1",
      output_precision: int = 2,
  ) -> str:
      """
      Get a line in Conversation Time Mark (CTM) format. Following CTM format appeared in `Rich Transcription Meeting Eval Plan: RT09` document.
  
      CTM Format:
          <SOURCE><SP><CHANNEL><SP><BEG-TIME><SP><DURATION><SP><TOKEN><SP><CONF><SP><TYPE><SP><SPEAKER><NEWLINE>
  
      Reference:
          https://web.archive.org/web/20170119114252/http://www.itl.nist.gov/iad/mig/tests/rt/2009/docs/rt09-meeting-eval-plan-v2.pdf
  
      Args:
          source (str): <SOURCE> is name of the source file, session name or utterance ID
          channel (int): <CHANNEL> is channel number defaults to 1
          start_time (float): <BEG_TIME> is the begin time of the word, which we refer to as `start_time` in NeMo.
          duration (float): <DURATION> is duration of the word
          token (str): <TOKEN> Token or word for the current entry
          conf (float): <CONF> is a floating point number between 0 (no confidence) and 1 (certainty). A value of “NA” is used (in CTM format data)
                        when no confidence is computed and in the reference data.
          type_of_token (str): <TYPE> is the token type. The legal values of <TYPE> are “lex”, “frag”, “fp”, “un-lex”, “for-lex”, “non-lex”, “misc”, or “noscore”
          speaker (str): <SPEAKER> is a string identifier for the speaker who uttered the token. This should be “null” for non-speech tokens and “unknown” when
                         the speaker has not been determined.
          NA_token (str, optional): A token for  . Defaults to '<NA>'.
          output_precision (int, optional): The precision of the output floating point number. Defaults to 3.
  
      Returns:
          str: Return a line in CTM format filled with the given information.
      """
      VALID_TOKEN_TYPES = [
          "lex",
          "frag",
          "fp",
          "un-lex",
          "for-lex",
          "non-lex",
          "misc",
          "noscore",
      ]
  
      if (
          type(start_time) == str
          and start_time.replace(".", "", 1).isdigit()
      ):
          start_time = float(start_time)
      elif type(start_time) != float:
          raise ValueError(
              f"`start_time` must be a float or str containing float, but got {type(start_time)}"
          )
  
      if (
          type(duration) == str
          and duration.replace(".", "", 1).isdigit()
      ):
          duration = float(duration)
      elif type(duration) != float:
          raise ValueError(
              f"`duration` must be a float or str containing float, but got {type(duration)}"
          )
  
      if type(conf) == str and conf.replace(".", "", 1).isdigit():
          conf = float(conf)
      elif conf is None:
          conf = NA_token
      elif type(conf) != float:
          raise ValueError(
              f"`conf` must be a float or str containing float, but got {type(conf)}"
          )
  
      if channel is not None and type(channel) != int:
          channel = str(channel)
      if (
          conf is not None
          and type(conf) == float
          and not (0 <= conf <= 1)
      ):
          raise ValueError(
              f"`conf` must be between 0 and 1, but got {conf}"
          )
      if type_of_token is not None and type(type_of_token) != str:
          raise ValueError(
              f"`type` must be a string, but got {type(type_of_token)} type {type_of_token}"
          )
      if (
          type_of_token is not None
          and type_of_token not in VALID_TOKEN_TYPES
      ):
          raise ValueError(
              f"`type` must be one of {VALID_TOKEN_TYPES}, but got {type_of_token} type {type_of_token}"
          )
      if speaker is not None and type(speaker) != str:
          raise ValueError(
              f"`speaker` must be a string, but got {type(speaker)}"
          )
  
      channel = default_channel if channel is None else channel
      conf = NA_token if conf is None else conf
      speaker = NA_token if speaker is None else speaker
      type_of_token = UNK if type_of_token is None else type_of_token
      start_time = get_rounded_str_float(start_time, output_precision)
      duration = get_rounded_str_float(duration, output_precision)
      conf = (
          get_rounded_str_float(conf, output_precision)
          if conf != NA_token
          else conf
      )
      return f"{source} {channel} {start_time} {duration} {token} {conf} {type_of_token} {speaker}\n"
  
imports: import json
  import os
  from collections import Counter
  from collections import OrderedDict
  from pathlib import Path
  from typing import Dict, List, Union
  import librosa
  import numpy
  from nemo.collections.asr.parts.utils.speaker_utils import audio_rttm_map, get_subsegments, get_uniqname_from_filepath, rttm_to_labels, segments_manifest_to_subsegments_manifest, write_rttm2manifest
  from nemo.utils.data_utils import DataStoreObject
label_desc: Use image node_id 2 for calling a global function with example usage: get_ctm_line(source, channel, start_time, duration, token, conf, type_of_token, speaker, NA_token, UNK, default_channel, output_precision) and returns: source, str, channel, str, start_time, str, duration, str, token, str, conf, str, type_of_token, str, speaker, str