whisperで音声認識を試したいが、エラーが出てしまう。

Question

前提

話題になっているwhisperで音声認識を試そうとしたところ以下のようなエラーが出ました。
ある動画から2分間の音声ファイルを抽出し、out_exe.mp3という名前で出力しました。
ファイルパスはgooglecolab上で/content/out_exe.mp3になっています。

実現したいこと

音声認識をできるようにしたい。

発生している問題・エラーメッセージ

Traceback (most recent call last)
<ipython-input-64-cad93362898e> in <module>
----> 1 model.transcribe("out_exe.mp3")

18 frames
/usr/local/lib/python3.7/dist-packages/whisper/transcribe.py in transcribe(model, audio, verbose, temperature, compression_ratio_threshold, logprob_threshold, no_speech_threshold, condition_on_previous_text, **decode_options)
     88             print("Detecting language using up to the first 30 seconds. Use `--language` to specify the language")
     89         segment = pad_or_trim(mel, N_FRAMES).to(model.device).to(dtype)
---> 90         _, probs = model.detect_language(segment)
     91         decode_options["language"] = max(probs, key=probs.get)
     92         if verbose is not None:

/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)
     25         def decorate_context(*args, **kwargs):
     26             with self.clone():
---> 27                 return func(*args, **kwargs)
     28         return cast(F, decorate_context)
     29 

/usr/local/lib/python3.7/dist-packages/whisper/decoding.py in detect_language(model, mel, tokenizer)
     59             for j, c in zip(tokenizer.all_language_tokens, tokenizer.all_language_codes)
     60         }
---> 61         for i in range(n_audio)
     62     ]
     63 

/usr/local/lib/python3.7/dist-packages/whisper/decoding.py in <listcomp>(.0)
     59             for j, c in zip(tokenizer.all_language_tokens, tokenizer.all_language_codes)
     60         }
---> 61         for i in range(n_audio)
     62     ]
     63 

/usr/local/lib/python3.7/dist-packages/whisper/tokenizer.py in all_language_codes(self)
    226     @lru_cache()
    227     def all_language_codes(self) -> Tuple[str]:
--> 228         return tuple(self.decode([l]).strip("<|>") for l in self.all_language_tokens)
    229 
    230     @property

/usr/local/lib/python3.7/dist-packages/whisper/tokenizer.py in <genexpr>(.0)
    226     @lru_cache()
    227     def all_language_codes(self) -> Tuple[str]:
--> 228         return tuple(self.decode([l]).strip("<|>") for l in self.all_language_tokens)
    229 
    230     @property

/usr/local/lib/python3.7/dist-packages/whisper/tokenizer.py in decode(self, token_ids, **kwargs)
    139 
    140     def decode(self, token_ids: Union[int, List[int], np.ndarray, torch.Tensor], **kwargs):
--> 141         return self.tokenizer.decode(token_ids, **kwargs)
    142 
    143     def decode_with_timestamps(self, tokens) -> str:

/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_base.py in decode(self, token_ids, skip_special_tokens, clean_up_tokenization_spaces, **kwargs)
   3428         """
   3429         # Convert inputs to python lists
-> 3430         token_ids = to_py_obj(token_ids)
   3431 
   3432         return self._decode(

/usr/local/lib/python3.7/dist-packages/transformers/utils/generic.py in to_py_obj(obj)
    115         return {k: to_py_obj(v) for k, v in obj.items()}
    116     elif isinstance(obj, (list, tuple)):
--> 117         return [to_py_obj(o) for o in obj]
    118     elif is_tf_available() and _is_tensorflow(obj):
    119         return obj.numpy().tolist()

/usr/local/lib/python3.7/dist-packages/transformers/utils/generic.py in <listcomp>(.0)
    115         return {k: to_py_obj(v) for k, v in obj.items()}
    116     elif isinstance(obj, (list, tuple)):
--> 117         return [to_py_obj(o) for o in obj]
    118     elif is_tf_available() and _is_tensorflow(obj):
    119         return obj.numpy().tolist()

/usr/local/lib/python3.7/dist-packages/transformers/utils/generic.py in to_py_obj(obj)
    116     elif isinstance(obj, (list, tuple)):
    117         return [to_py_obj(o) for o in obj]
--> 118     elif is_tf_available() and _is_tensorflow(obj):
    119         return obj.numpy().tolist()
    120     elif is_torch_available() and _is_torch(obj):

/usr/local/lib/python3.7/dist-packages/transformers/utils/generic.py in _is_tensorflow(x)
     97 
     98 def _is_tensorflow(x):
---> 99     import tensorflow as tf
    100 
    101     return isinstance(x, tf.Tensor)

/usr/local/lib/python3.7/dist-packages/tensorflow/__init__.py in <module>
     35 import typing as _typing
     36 
---> 37 from tensorflow.python.tools import module_util as _module_util
     38 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
     39 

/usr/local/lib/python3.7/dist-packages/tensorflow/python/__init__.py in <module>
     35 
     36 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
---> 37 from tensorflow.python.eager import context
     38 
     39 # pylint: enable=wildcard-import

/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/context.py in <module>
     27 import six
     28 
---> 29 from tensorflow.core.framework import function_pb2
     30 from tensorflow.core.protobuf import config_pb2
     31 from tensorflow.core.protobuf import coordination_config_pb2

/usr/local/lib/python3.7/dist-packages/tensorflow/core/framework/function_pb2.py in <module>
     14 
     15 
---> 16 from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
     17 from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2
     18 from tensorflow.core.framework import op_def_pb2 as tensorflow_dot_core_dot_framework_dot_op__def__pb2

/usr/local/lib/python3.7/dist-packages/tensorflow/core/framework/attr_value_pb2.py in <module>
     14 
     15 
---> 16 from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
     17 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
     18 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2

/usr/local/lib/python3.7/dist-packages/tensorflow/core/framework/tensor_pb2.py in <module>
     14 
     15 
---> 16 from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
     17 from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
     18 from tensorflow.core.framework import types_pb2 as tensorflow_dot_core_dot_framework_dot_types__pb2

/usr/local/lib/python3.7/dist-packages/tensorflow/core/framework/resource_handle_pb2.py in <module>
    148   ,
    149   'DESCRIPTOR' : _RESOURCEHANDLEPROTO,
--> 150   '__module__' : 'tensorflow.core.framework.resource_handle_pb2'
    151   # @@protoc_insertion_point(class_scope:tensorflow.ResourceHandleProto)
    152   })

SystemError:google/protobuf/pyext/descriptor.cc:358: bad argument to internal function

該当のソースコード

import whisper

model = whisper.load_model("base")
print(model.transcribe("out_exe.mp3"))

Comments

[8524ba23]

もしエラー詳細（traceback）があれば、それも記載ください。

[mai_yoko]

更新いたしました

[jbpb0]

「Traceback」と書かれてるところからエラーメッセージまでの間に表示されてるものを全部、できるだけ省略せずに質問に記載してください
(ユーザー名等の個人情報は伏せ字で)

Answer 1

まずはこちらで試したところcolab上でエラーは再現しませんでした。

ただエラー詳細から、内部でtensorflowが使われているようです。
そのうえでエラーメッセージで検索すると以下が見つかりました。
"SystemError: google/protobuf/pyext/descriptor.cc:358: bad argument to internal function" while using Audio Transformers in Hugging Face
この回答によると先頭にimport tensorflow as tfのようにimportを使うと回避できるようです。