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import numpy as np
import librosa
import io
from .init import pipe
TASK = "transcribe"
BATCH_SIZE = 8
class A2T:
def __init__(self, mic):
self.mic = mic
def __generate_text(self, inputs, task: str = None):
if inputs is None:
raise Exception("Inputs is None")
transcribed_text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
return transcribed_text
def __preprocces(self, raw: bytes):
print(f"Raw type : {type(raw)}")
chunk = io.BytesIO(raw)
audio, sample_rate = librosa.load(chunk, sr=16000)
print(f"Sample rate : {sample_rate}")
return audio
def predict(self):
try:
if self.mic is not None:
raw = self.mic
audio = self.__preprocces(raw=raw)
print(f"audio type : {type(audio)} \n shape : {audio.shape} \n audio max value : {np.max(audio)}")
else:
raise Exception("please provide audio")
if isinstance(audio , np.ndarray):
return self.__generate_text(inputs=audio, task=TASK)
else:
raise Exception("Audio is not np array")
except Exception as e:
return f"Oops some kinda error : {e}" |