Deep learning for environmentally robust speech recognition: An overview of recent developments
Eliminating the negative effect of non-stationary environmental noise is a long-standing
research topic for automatic speech recognition but still remains an important challenge …
research topic for automatic speech recognition but still remains an important challenge …
A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications
This paper attempts to identify the requirement and the development of machine learning‐
based mobile big data (MBD) analysis through discussing the insights of challenges in the …
based mobile big data (MBD) analysis through discussing the insights of challenges in the …
Text-independent speaker verification based on triplet convolutional neural network embeddings
The effectiveness of introducing deep neural networks into conventional speaker recognition
pipelines has been broadly shown to benefit system performance. A novel text-independent …
pipelines has been broadly shown to benefit system performance. A novel text-independent …
Sequence summarizing neural network for speaker adaptation
In this paper, we propose a DNN adaptation technique, where the i-vector extractor is
replaced by a Sequence Summarizing Neural Network (SSNN). Similarly to i-vector …
replaced by a Sequence Summarizing Neural Network (SSNN). Similarly to i-vector …
Factorized hidden layer adaptation for deep neural network based acoustic modeling
In this paper, we propose the factorized hidden layer (FHL) approach to adapt the deep
neural network (DNN) acoustic models for automatic speech recognition (ASR). FHL aims at …
neural network (DNN) acoustic models for automatic speech recognition (ASR). FHL aims at …
Context adaptive deep neural networks for fast acoustic model adaptation in noisy conditions
Deep neural network (DNN) based acoustic models have greatly improved the performance
of automatic speech recognition (ASR) for various tasks. Further performance improvements …
of automatic speech recognition (ASR) for various tasks. Further performance improvements …
A study of speaker verification performance with expressive speech
Expressive speech introduces variations in the acoustic features affecting the performance
of speech technology such as speaker verification systems. It is important to identify the …
of speech technology such as speaker verification systems. It is important to identify the …
Predicting speaker recognition reliability by considering emotional content
Studies have shown that emotional variability in speech degrades the performance of
speaker recognition tasks. Of particular interest is the error produced due to mismatch …
speaker recognition tasks. Of particular interest is the error produced due to mismatch …
[PDF][PDF] 2016 BUT Babel System: Multilingual BLSTM Acoustic Model with i-Vector Based Adaptation.
The paper provides an analysis of BUT automatic speech recognition systems (ASR) built for
the 2016 IARPA Babel evaluation. The IARPA Babel program concentrates on building ASR …
the 2016 IARPA Babel evaluation. The IARPA Babel program concentrates on building ASR …
Robust feature extraction and uncertainty estimation based on attractor dynamics in cyclic deep denoising autoencoders
Because the input and the output values of the deep denoising autoencoders (DDAs) have
the same representation space, the output values of a DDA can be used as its input values …
the same representation space, the output values of a DDA can be used as its input values …