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BarVox Audio Processing API - Model Loader Module
VERSION 2.2: Includes Wav2Vec2 CTC and base models
"""
import logging
import torch
logger = logging.getLogger(__name__)
_MODELS = {}
def load_models():
"""Load all required models into memory."""
global _MODELS
logger.info("Loading models...")
# HuBERT CTC
from transformers import Wav2Vec2Processor, HubertForCTC, HubertModel
_MODELS['hubert_processor'] = Wav2Vec2Processor.from_pretrained("facebook/hubert-large-ls960-ft")
_MODELS['hubert_model'] = HubertForCTC.from_pretrained("facebook/hubert-large-ls960-ft")
_MODELS['hubert_base_model'] = HubertModel.from_pretrained("facebook/hubert-large-ls960-ft")
logger.info("✓ HuBERT models loaded")
# Wav2Vec2 CTC
from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC, Wav2Vec2Model
_MODELS['wav2vec2_processor'] = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-large-960h-lv60-self")
_MODELS['wav2vec2_model'] = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h-lv60-self")
_MODELS['wav2vec2_base_model'] = Wav2Vec2Model.from_pretrained("facebook/wav2vec2-large-960h-lv60-self")
logger.info("✓ Wav2Vec2 models loaded")
# TRILL
try:
import tensorflow_hub as hub
_MODELS['trill_model'] = hub.load('https://tfhub.dev/google/nonsemantic-speech-benchmark/trill/3')
logger.info("✓ TRILL model loaded")
except Exception as e:
logger.warning(f"TRILL model failed to load (non-fatal): {e}")
# Silero VAD
silero_model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad', model='silero_vad', force_reload=False, trust_repo=True)
_MODELS['silero_vad'] = silero_model
_MODELS['silero_utils'] = utils
logger.info("✓ Silero VAD loaded")
# Allosaurus
try:
from allosaurus.app import read_recognizer
_MODELS['allosaurus_model'] = read_recognizer()
logger.info("✓ Allosaurus loaded")
except Exception as e:
logger.warning(f"Allosaurus model failed to load (non-fatal): {e}")
logger.info("All models loaded successfully!")
def get_models():
"""Get the loaded models dictionary."""
return _MODELS |