Wi-Fi positioning has drawn great attention in the field of indoor positioning, due to its low
cost, easy deployment, and large positioning range. However, the Wi-Fi signal is highly …

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for
understanding these methods generated. Existing Python programming packages for …

Recurrent neural networks (RNNs) are powerful in the tasks oriented to sequential data,
such as natural language processing and video recognition. However, because the modern …

Quantifying the confidence (or conversely the uncertainty) of a prediction is a highly
desirable trait of an automatic system, as it improves the robustness and usefulness in …

The standard approach to assess reliability of automatic speech transcriptions is through the
use of confidence scores. If accurate, these scores provide a flexible mechanism to flag …

In this paper, we present techniques to compute confidence score on the predictions made
by an end-to-end speech recognition model. Our proposed neural confidence measure …

Temperature monitoring is critical for electrical motors to determine if device protection
measures should be executed. However, the complexity of the internal structure of …

The standard approach to mitigate errors made by an automatic speech recognition system
is to use confidence scores associated with each predicted word. In the simplest case, these …

End-to-end models with auto-regressive decoders have shown impressive results for
automatic speech recognition (ASR). These models formulate the sequence-level probability …

As the modern deep neural networks (DNNs) have become more and more large-scale and
expensive, the topic of DNN compression grows into a hot direction nowadays. Among …