Very deep multilingual convolutional neural networks for LVCSR
Convolutional neural networks (CNNs) are a standard component of many current state-of-
the-art Large Vocabulary Continuous Speech Recognition (LVCSR) systems. However …
the-art Large Vocabulary Continuous Speech Recognition (LVCSR) systems. However …
[PDF][PDF] Recurrent Neural Network Based Language Modeling in Meeting Recognition.
We use recurrent neural network (RNN) based language models to improve the BUT
English meeting recognizer. On the baseline setup using the original language models we …
English meeting recognizer. On the baseline setup using the original language models we …
[PDF][PDF] Neural Network Bottleneck Features for Language Identification.
This paper presents the application of Neural Network Bottleneck (BN) features in Language
Identification (LID). BN features are generally used for Large Vocabulary Speech …
Identification (LID). BN features are generally used for Large Vocabulary Speech …
Multilingual representations for low resource speech recognition and keyword search
This paper examines the impact of multilingual (ML) acoustic representations on Automatic
Speech Recognition (ASR) and keyword search (KWS) for low resource languages in the …
Speech Recognition (ASR) and keyword search (KWS) for low resource languages in the …
Multilingually trained bottleneck features in spoken language recognition
Multilingual training of neural networks has proven to be simple yet effective way to deal with
multilingual training corpora. It allows to use several resources to jointly train a language …
multilingual training corpora. It allows to use several resources to jointly train a language …
[HTML][HTML] On the use of deep feedforward neural networks for automatic language identification
In this work, we present a comprehensive study on the use of deep neural networks (DNNs)
for automatic language identification (LID). Motivated by the recent success of using DNNs …
for automatic language identification (LID). Motivated by the recent success of using DNNs …
Transcribing meetings with the AMIDA systems
In this paper, we give an overview of the AMIDA systems for transcription of conference and
lecture room meetings. The systems were developed for participation in the Rich …
lecture room meetings. The systems were developed for participation in the Rich …
Adaptation of multilingual stacked bottle-neck neural network structure for new language
The neural network based features became an inseparable part of state-of-the-art LVCSR
systems. In order to perform well, the network has to be trained on a large amount of in …
systems. In order to perform well, the network has to be trained on a large amount of in …
HMM-based phrase-independent i-vector extractor for text-dependent speaker verification
The low-dimensional i-vector representation of speech segments is used in the state-of-the-
art text-independent speaker verification systems. However, i-vectors were deemed …
art text-independent speaker verification systems. However, i-vectors were deemed …
Using neural network front-ends on far field multiple microphones based speech recognition
This paper presents an investigation of far field speech recognition using beamforming and
channel concatenation in the context of Deep Neural Network (DNN) based feature …
channel concatenation in the context of Deep Neural Network (DNN) based feature …