[PDF][PDF] An Improved Goodness of Pronunciation (GoP) Measure for Pronunciation Evaluation with DNN-HMM System Considering HMM Transition Probabilities.
Goodness of pronunciation (GoP) is typically formulated with Gaussian mixture model-
hidden Markov model (GMM-HMM) based acoustic models considering HMM state transition …
hidden Markov model (GMM-HMM) based acoustic models considering HMM state transition …
Unsupervised pre-trained filter learning approach for efficient convolution neural network
Abstract The concept of Convolution Neural Network (ConvNet or CNN) is evaluated from
the animal visual cortex. Since humans can learn through experience, similarly, ConvNet …
the animal visual cortex. Since humans can learn through experience, similarly, ConvNet …
Multiple proposals for continuous arabic sign language recognition
The deaf community relies on sign language as the primary means of communication. For
the millions of people around the world who suffer from hearing loss, interaction with hearing …
the millions of people around the world who suffer from hearing loss, interaction with hearing …
GFCC based discriminatively trained noise robust continuous ASR system for Hindi language
A statistically designed Automatic Speech Recognition (ASR) system extracts features from
speech signals using feature extraction methods, links the extracted features with the …
speech signals using feature extraction methods, links the extracted features with the …
Bi-directional lattice recurrent neural networks for confidence estimation
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 …
is to use confidence scores associated with each predicted word. In the simplest case, these …
Discriminative training using noise robust integrated features and refined HMM modeling
The classical approach to build an automatic speech recognition (ASR) system uses
different feature extraction methods at the front end and various parameter classification …
different feature extraction methods at the front end and various parameter classification …
Integrating source-channel and attention-based sequence-to-sequence models for speech recognition
This paper proposes a novel automatic speech recognition (ASR) framework called
Integrated Source-Channel and Attention (ISCA) that combines the advantages of traditional …
Integrated Source-Channel and Attention (ISCA) that combines the advantages of traditional …
Challenging the boundaries of speech recognition: the MALACH corpus
There has been huge progress in speech recognition over the last several years. Tasks
once thought extremely difficult, such as SWITCHBOARD, now approach levels of human …
once thought extremely difficult, such as SWITCHBOARD, now approach levels of human …
Promising accurate prefix boosting for sequence-to-sequence asr
In this paper, we present promising accurate prefix boosting (PAPB), a discriminative
training technique for attention based sequence-to-sequence (seq2seq) ASR. PAPB is …
training technique for attention based sequence-to-sequence (seq2seq) ASR. PAPB is …
PyHTK: Python library and ASR pipelines for HTK
This paper describes PyHTK, which is a Python-based library and associated pipeline to
facilitate the construction of large-scale complex automatic speech recognition (ASR) …
facilitate the construction of large-scale complex automatic speech recognition (ASR) …