In this paper we describe a method to perform sequencediscriminative training of neural network acoustic models without the need for frame-level cross-entropy pre-training. We use the lattice-free… (More)
Long Short-Term Memory networks (LSTMs) are a component of many state-of-the-art DNN-based speech recognition systems. Dropout is a popular method to improve generalization in DNN training. In this… (More)
Provides an overview of a speech-to-text (STT) and keyword search (KWS) system architecture build primarily on the top of the Kaldi toolkit and expands on a few highlights. The system was developed… (More)
Most speech recognition systems use spectral features based on fixed filters, such as MFCC and PLP. In this paper, we show that it is possible to achieve state of the art results by making the… (More)
Multi-style training, using data which emulates a variety of possible test scenarios, is a popular approach towards robust acoustic modeling. However acoustic models capable of exploiting large… (More)
2016 IEEE International Conference on Acoustics…
2016
Mismatched transcriptions of speech in a target language refers to transcriptions provided by people unfamiliar with the language, using English letter sequences. In this work, we demonstrate the… (More)
In many under-resourced languages it is possible to find text, and it is possible to find speech, but transcribed speech suitable for training automatic speech recognition ASR is unavailable. In the… (More)
In this paper, we propose a new acoustic modeling technique called the Phone-Cluster Adaptive Training. In this approach, the parameters of context-dependent states are obtained by the linear… (More)
It is common in applications of ASR to have a large amount of data out-of-domain to the test data and a smaller amount of in-domain data similar to the test data. In this paper, we investigate… (More)
In far-field speech recognition systems, training acoustic models with alignments generated from parallel close-talk microphone data provides significant improvements. However it is not practical to… (More)