Transcript an Spanish audio
How I can select the language Spanish to has a better transcription?
I have an example but give errors:
import whisper
Cargar el modelo Whisper (usaremos el modelo 'base' como ejemplo)
model = whisper.load_model("base")
Ruta al archivo de audio en español
audio_path = r'C:\Users\andre\Downloads\Example.wav'
Cargar el audio
audio = whisper.load_audio(audio_path)
Convertir a espectrograma log-Mel y mover al mismo dispositivo que el modelo
mel = whisper.log_mel_spectrogram(audio).to(model.device)
Detectar el idioma hablado (opcional)
_, probs = model.detect_language(mel)
detected_language = max(probs, key=probs.get)
print(f"Idioma detectado: {detected_language}")
Decodificar el audio
options = whisper.DecodingOptions(language="es") # Indicar que el idioma es español
result = whisper.decode(model, mel, options)
Imprimir el texto reconocido
print(result.text)
Hey @Andrews99 , you can do this in Transformers with the following steps. First, install Transformers:
pip install -U transformers accelerate
Then, run the following code snippet:
import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
from datasets import load_dataset
device = "cuda:0" if torch.cuda.is_available() else "cpu"
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
model_id = "openai/whisper-large-v3"
model = AutoModelForSpeechSeq2Seq.from_pretrained(
model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
)
model.to(device)
processor = AutoProcessor.from_pretrained(model_id)
pipe = pipeline(
"automatic-speech-recognition",
model=model,
tokenizer=processor.tokenizer,
feature_extractor=processor.feature_extractor,
max_new_tokens=128,
chunk_length_s=30,
batch_size=16,
return_timestamps=True,
torch_dtype=torch_dtype,
device=device,
)
audio_path = r'C:\Users\andre\Downloads\Example.wav'
result = pipe(audio_path, generate_kwargs={"language": "es", "task": "transcribe"})
print(result["text"])
Alternatively, in OpenAI Whisper you can do:
import torch
from whisper import load_model, transcribe
model = load_model("large-v3")
audio_path = r'C:\Users\andre\Downloads\Example.wav'
pred_out = transcribe(model, audio= audio_path, language="es")
print(pred_out["text"])
Alternatively, in OpenAI Whisper you can do:
import torch from whisper import load_model, transcribe model = load_model("large-v3") audio_path = r'C:\Users\andre\Downloads\Example.wav' pred_out = transcribe(model, audio= audio_path, language="es") print(pred_out["text"])
Thank you! I have a better understanding 🙏