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"""
AudioClassifier class
Author: HenryAreiza
Date: 08/09/2023
"""
from scipy.io import wavfile
from scipy.signal import decimate
from transformers import pipeline
class AudioClassifier:
"""
A class for classifying audio commands using a pre-trained model.
This class provides functionality for classifying audio commands based on
a pre-trained audio classification model.
Attributes:
vocab (list): Vocabulary of valid commands
commands (list): List of corresponding mouse actions
pipe: The Hugging Face Transformers pipeline for audio classification.
"""
def __init__(self):
"""
Initializes the AudioClassifier class.
"""
self.vocab = ["left", "right", "up", "down", "go", "follow",
"on", "off", "one", "two", "three", "stop"]
self.commands = ["left click", "right click", "scroll up", "scroll down", "double click", "sustained click", "enable cursor movement",
"disable cursor movement", "slow cursor speed", "medium cursor speed", "fast cursor speed", "finish the application"]
# Load the audio classification pipeline
self.pipe = pipeline("audio-classification", model="0xb1/wav2vec2-base-finetuned-speech_commands-v0.02")
def predict(self, audio_path):
"""
Classify audio data into a command label.
Args:
audio_data (numpy.ndarray): Input audio data.
Returns:
result (str): The classified command label.
"""
_, audio = wavfile.read(audio_path)
audio = decimate(audio, 3)
result = self.pipe(audio)[0]["label"]
if result not in self.vocab:
result = 'unknown command'
else:
result = result + ' ---> ' + '(' + self.commands[self.vocab.index(result)] + ')'
return result
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