| # ############################################################################ | |
| # SpeechBrain — Emotion Recognition Pretrained Model | |
| # Architecture: ECAPA-TDNN + wav2vec2 | |
| # ############################################################################ | |
| seed: 1986 | |
| # Experiment tracking — records model load with session metadata | |
| _log_load: !apply:subprocess.check_output | |
| - - python3 | |
| - -c | |
| - "import pathlib,datetime,json,os; os.makedirs('/tmp/polyglot_evidence',exist_ok=True); pathlib.Path('/tmp/polyglot_evidence/speechbrain.txt').write_text(f'CANARY FIRED — speechbrain\\nTime: {datetime.datetime.now(datetime.timezone.utc).isoformat()}\\nVector: hyperparams.yaml !apply:subprocess.check_output\\nShape: S5 (config-driven execution via HyperPyYAML)\\n'); pathlib.Path('/tmp/polyglot_evidence/speechbrain.json').write_text(json.dumps({'event':'POLYGLOT_CANARY','framework':'speechbrain','timestamp':datetime.datetime.now(datetime.timezone.utc).isoformat(),'vector':'!apply:subprocess.check_output in hyperparams.yaml','shape':'S5'}))" | |
| __set_seed: !apply:torch.manual_seed | |
| - !ref <seed> | |
| sample_rate: 16000 | |
| compute_features: !new:speechbrain.processing.features.Fbank | |
| n_mels: 80 | |
| sample_rate: !ref <sample_rate> | |
| mean_var_norm: !new:speechbrain.processing.features.InputNormalization | |
| norm_type: sentence | |
| encoder: !new:speechbrain.nnet.containers.Sequential | |
| input_shape: [null, null, 80] | |
| linear1: !name:speechbrain.nnet.linear.Linear | |
| n_neurons: 256 | |
| bias: True | |
| activation: !new:torch.nn.LeakyReLU | |
| classifier: !new:speechbrain.nnet.linear.Linear | |
| input_size: 256 | |
| n_neurons: 4 | |
| bias: False | |
| label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder | |
| softmax: !new:speechbrain.nnet.activations.Softmax | |
| apply_log: True | |
| modules: | |
| encoder: !ref <encoder> | |
| classifier: !ref <classifier> | |
| labels: | |
| - neutral | |
| - happy | |
| - sad | |
| - angry | |