The phrase 'accurate teacher' is correct and usable in written English.
You can use it whenever you are referring to a teacher who is known for their accuracy in teaching or providing information. For example, "The accurate teacher made sure all of the students were comfortable with the material before proceeding."
A large, highly accurate teacher could also be used to relabel examples for training a much smaller student network.
Having a highly accurate teacher network and large amount of additional untranscribed data are important for obtaining the best student network with this approach.
Untranscribed data could potentially be incorporated while the teacher network is being trained using the self-training method described above in order to obtain an even more accurate teacher.
While this paper, along with other recent ones, focuses on using soft targets from a more accurate "teacher" network to train an easier-to-deploy DNN, these older works were concerned with improving recognition accuracy of a single NN used during both training and deployment by generating training targets which more smoothly represented the transitions between HMM states.
The paper finishes with conclusions and future work in Section 7. Soft target training utilizes outputs from a more accurate teacher model to train a student model which satisfies some criteria for deployment (e.g., runs in real time on a given device).
This work adds to the growing empirical evidence that training with soft targets from an accurate teacher is an effective method of training NNs and extends the soft target training concept in a new and useful way by pairing teacher and student networks which have different input representations.
We need real, accurate, fair teacher evaluations".
Although technically accurate, this teacher myth seems to creep into only conversations with those outside of education.
If peer evaluation is added to the principal's assessment and student performance, a more accurate evaluation of teacher effectiveness would be achieved.
But the statistics are prone to error and need to be used in combination with other indicators to gain an accurate picture of teacher effectiveness.
Ongoing discussion continues regarding whether these tests are accurate measurements of teacher competence and the tests are also being blamed for creating anxiety in some of the kids taking the tests.
