def METHOD_NAME(**kwargs):
    asr_dummy = None
    if framework in ("tensorflow2v1", "tensorflow2"):
        class TensorFlowV2ASRDummy(TensorFlowV2Estimator, SpeechRecognizerMixin):
            def get_activations(self):
                pass
            def predict(self, x):
                pass
            def loss_gradient(self, x, y, **kwargs):
                return x
            @property
            def input_shape(self):
                return None
            def compute_loss(self, x, y, **kwargs):
                pass
        asr_dummy = TensorFlowV2ASRDummy(channels_first=None, model=None, clip_values=None)
    if framework == "pytorch":
        class PyTorchASRDummy(PyTorchEstimator, SpeechRecognizerMixin):
            def get_activations(self):
                pass
            def predict(self, x):
                pass
            def loss_gradient(self, x, y, **kwargs):
                return x
            @property
            def input_shape(self):
                return None
            def compute_loss(self, x, y, **kwargs):
                pass
        asr_dummy = PyTorchASRDummy(channels_first=None, model=None, clip_values=None)
    if asr_dummy is None:
        raise ARTTestFixtureNotImplemented(
            "ASR dummy estimator not available for this framework", asr_dummy_estimator.__name__, framework
        )
    return asr_dummy