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I am trying to generate a transcription for an mp3 audio in Arabic language, while following the instructions.
but sentence return empty list.
sentences = doc.transcript(include_tiers=False, strip=True)
print(sentences)
Note: The below lines were removed due to IndexError: list index out of range
When adding those lines for detailed transcription, the program never terminated (infinite loop)
nlp = ba.BatchalignPipeline.new("asr,morphosyntax", lang="ara", num_speakers=2)
doc1 = nlp(doc) # this is equivalent to nlp("audio.mp3"), we will make the initial doc for you
**Note: before the getting into infinite loop the following lines were displayed at the terminal **
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.ngs are fine-tuned or trained. _attentiondoes not supportoutput_attenti
WhisperModel is using WhisperSdpaAttention, but torch.nn.functional.scaled_dot_productation, but specifying the manual implementat_attention does not support output_attentions=True or layer_head_mask not None. Faved using the argument attn_implementation=lling back to the manual attention implementation, but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument attn_implementation="eager"` when loading the model.
The text was updated successfully, but these errors were encountered:
I am trying to generate a transcription for an mp3 audio in Arabic language, while following the instructions.
but sentence return empty list.
sentences = doc.transcript(include_tiers=False, strip=True)
print(sentences)
Note: The below lines were removed due to IndexError: list index out of range
first_utterance = doc[0]
first_form = doc[0][0]
the_comma = doc[0][1]
assert the_comma.text == ','
assert the_comma.type == ba.TokenType.PUNCT
When adding those lines for detailed transcription, the program never terminated (infinite loop)
nlp = ba.BatchalignPipeline.new("asr,morphosyntax", lang="ara", num_speakers=2)
doc1 = nlp(doc) # this is equivalent to nlp("audio.mp3"), we will make the initial doc for you
first_word_pos = doc1[0][0].morphology
first_word_time = doc1[0][0].time
first_utterance_time = doc1[0].alignment
**Note: before the getting into infinite loop the following lines were displayed at the terminal **
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.ngs are fine-tuned or trained. _attention
does not support
output_attentiWhisperModel is using WhisperSdpaAttention, but
torch.nn.functional.scaled_dot_productation, but specifying the manual implementat_attention
does not supportoutput_attentions=True
orlayer_head_mask
not None. Faved using the argumentattn_implementation=lling back to the manual attention implementation, but specifying the manual implementation will be required from Transformers version v5.0.0 onwards. This warning can be removed using the argument
attn_implementation="eager"` when loading the model.The text was updated successfully, but these errors were encountered: