code: def test_simple_whisper_translation(self):
      speech_recognizer = pipeline(
          task="automatic-speech-recognition",
          model="openai/whisper-large",
          framework="pt",
      )
      ds = load_dataset(
          "hf-internal-testing/librispeech_asr_dummy",
          "clean",
          split="validation",
      ).sort("id")
      filename = ds[40]["file"]
      output = speech_recognizer(filename)
      self.assertEqual(
          output, {"text": " A man said to the universe, Sir, I exist."}
      )
  
      model = WhisperForConditionalGeneration.from_pretrained(
          "openai/whisper-large"
      )
      tokenizer = AutoTokenizer.from_pretrained("openai/whisper-large")
      feature_extractor = AutoFeatureExtractor.from_pretrained(
          "openai/whisper-large"
      )
  
      speech_recognizer_2 = AutomaticSpeechRecognitionPipeline(
          model=model,
          tokenizer=tokenizer,
          feature_extractor=feature_extractor,
      )
      output_2 = speech_recognizer_2(filename)
      self.assertEqual(output, output_2)
  
      processor = WhisperProcessor(feature_extractor, tokenizer)
      model.config.forced_decoder_ids = (
          processor.get_decoder_prompt_ids(
              task="transcribe", language="it"
          )
      )
      speech_translator = AutomaticSpeechRecognitionPipeline(
          model=model,
          tokenizer=tokenizer,
          feature_extractor=feature_extractor,
      )
      output_3 = speech_translator(filename)
      self.assertEqual(
          output_3,
          {"text": " Un uomo ha detto allo universo, Sir, esiste."},
      )
  
imports: import unittest
  import numpy
  import pytest
  from datasets import load_dataset
  from huggingface_hub import snapshot_download
  from transformers import MODEL_FOR_CTC_MAPPING, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, AutoFeatureExtractor, AutoTokenizer, Speech2TextForConditionalGeneration, Wav2Vec2ForCTC, WhisperForConditionalGeneration, WhisperProcessor
  from transformers.pipelines import AutomaticSpeechRecognitionPipeline, pipeline
  from transformers.pipelines.audio_utils import chunk_bytes_iter
  from transformers.pipelines.automatic_speech_recognition import chunk_iter
  from transformers.testing_utils import is_torch_available, nested_simplify, require_pyctcdecode, require_tf, require_torch, require_torchaudio, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 14 for calling the AutomaticSpeechRecognitionPipelineTests obj's underlying member method code with example usage: obj.test_simple_whisper_translation() without return types