Abstract Language models play an important role in large vocabulary speech recognition
and statistical machine translation systems. The dominant approach since several decades …

This paper extends a novel neural network language model (NNLM) which relies on word
clustering to structure the output vocabulary: Structured OUtput Layer (SOUL) NNLM. This …

Conventional wisdom in automatic speech recognition asserts that pitch information is not
helpful in building speech recognizers for non-tonal languages and contributes only …

This study aims to increase our knowledge of Mandarin lexical tone duration in continuous
Mandarin speech. Related variation factors such as the number of syllable (s) in word, the …

Fundamental modelling differences between hybrid and end-to-end (E2E) automatic speech
recognition (ASR) systems create large diversity and complementarity among them. This …

The paper describes a neural network language model that jointly models language in many
related domains. In addition to the traditional layers of a neural network language model, the …

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often
combine outputs from multiple sub-systems that may even be developed at different sites …

Many of the world's languages are falling out of use without a written record and minimal
linguistic documentation. Language documentation is a slow process and there are an …

This paper presents recent progress in developing speech-totext (STT) and keyword
spotting (KWS) systems for the 2014 IARPA-Babel evaluation. Systems have been …

This paper describes a very efficient Parallel Phone Recognizers followed by Language
Modeling (PPRLM) system in terms of both performance and processing speed. The system …