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Error detection and accuracy estimation in automatic speech recognition using deep bidirectional recurrent neural networks
Recurrent neural networks (RNNs) have recently been applied as the classifiers for
sequential labeling problems. In this paper, deep bidirectional RNNs (DBRNNs) are applied …
sequential labeling problems. In this paper, deep bidirectional RNNs (DBRNNs) are applied …
Estimating confidence scores on ASR results using recurrent neural networks
In this paper we present a confidence estimation system using recurrent neural networks
(RNN) and compare it to a traditional multilayered perception (MLP) based system. The …
(RNN) and compare it to a traditional multilayered perception (MLP) based system. The …
Analyzing uncertainties in speech recognition using dropout
The performance of Automatic Speech Recognition (ASR) systems is often measured using
Word Error Rates (WER) which requires time-consuming and expensive manually …
Word Error Rates (WER) which requires time-consuming and expensive manually …
[PDF][PDF] Combining information sources for confidence estimation with CRF models
Obtaining accurate confidence measures for automatic speech recognition (ASR)
transcriptions is an important task which stands to benefit from the use of multiple …
transcriptions is an important task which stands to benefit from the use of multiple …
ASR error detection and recognition rate estimation using deep bidirectional recurrent neural networks
Recurrent neural networks (RNNs) have recently been applied as the classifiers for
sequential labeling problems. In this paper, deep bidirectional RNNs (DBRNNs) are applied …
sequential labeling problems. In this paper, deep bidirectional RNNs (DBRNNs) are applied …
Enhancing lexical cohesion measure with confidence measures, semantic relations and language model interpolation for multimedia spoken content topic …
Transcript-based topic segmentation of TV programs faces several difficulties arising from
transcription errors, from the presence of potentially short segments and from the limited …
transcription errors, from the presence of potentially short segments and from the limited …
System-independent asr error detection and classification using recurrent neural network
This paper addresses errors in continuous Automatic Speech Recognition (ASR) in two
stages: error detection and error type classification. Unlike the majority of research in this …
stages: error detection and error type classification. Unlike the majority of research in this …
Estimating speech recognition accuracy based on error type classification
Methods for estimating the speech recognition accuracy without using manually transcribed
references are beneficial to the research and development of automatic speech recognition …
references are beneficial to the research and development of automatic speech recognition …
Speaker-adapted confidence measures for speech recognition of video lectures
Automatic speech recognition applications can benefit from a confidence measure (CM) to
predict the reliability of the output. Previous works showed that a word-dependent naïve …
predict the reliability of the output. Previous works showed that a word-dependent naïve …
An empirical study of software exceptions in the field using search logs
Background: Software engineers spend a substantial amount of time using Web search to
accomplish software engineering tasks. Such search tasks include finding code snippets …
accomplish software engineering tasks. Such search tasks include finding code snippets …