Open AccessProceedings Article
Julius --- An Open Source Real-Time Large Vocabulary Recognition Engine
Akinobu Lee,Tatsuya Kawahara,Kiyohiro Shikano +2 more
- Vol. 3, pp 1691-1694
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TLDR
EUROSPEECH2001: the 7th European Conference on Speech Communication and Technology, September 3-7, 2001, Aalborg, Denmark.Abstract:
EUROSPEECH2001: the 7th European Conference on Speech Communication and Technology, September 3-7, 2001, Aalborg, Denmark.read more
Citations
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The Kaldi Speech Recognition Toolkit
Daniel Povey,Arnab Ghoshal,Gilles Boulianne,Lukas Burget,Ondrej Glembek,Nagendra Kumar Goel,Mirko Hannemann,Petr Motlicek,Yanmin Qian,Petr Schwarz,Jan Silovsky,Georg Stemmer,Karel Vesely +12 more
TL;DR: The design of Kaldi is described, a free, open-source toolkit for speech recognition research that provides a speech recognition system based on finite-state automata together with detailed documentation and a comprehensive set of scripts for building complete recognition systems.
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ESPNet: End-to-end speech processing toolkit
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TL;DR: In this article, a new open source platform for end-to-end speech processing named ESPnet is introduced, which mainly focuses on automatic speech recognition (ASR), and adopts widely used dynamic neural network toolkits, Chainer and PyTorch, as a main deep learning engine.
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Recent Development of Open-Source Speech Recognition Engine Julius
Akinobu Lee,Tatsuya Kawahara +1 more
TL;DR: An overview of Julius, major features and specifications are described, and the developments conducted in the recent years are summarized.
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ModDrop: Adaptive Multi-Modal Gesture Recognition
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References
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The HTK book
TL;DR: The Fundamentals of HTK: General Principles of HMMs, Recognition and Viterbi Decoding, and Continuous Speech Recognition.
Proceedings Article
Statistical Language Modeling using the CMU-Cambridge Toolkit
Philip Clarkson,Ronald Rosenfeld +1 more
TL;DR: The CMU Statistical Language Modeling toolkit was re leased in in order to facilitate the construction and testing of bigram and trigram language models and the technology as implemented in the toolkit is outlined.
Proceedings Article
Free software toolkit for Japanese large vocabulary continuous speech recognition
Tatsuya Kawahara,Akinobu Lee,Tetsunori Kobayashi,Kazuya Takeda,Nobuaki Minematsu,Shigeki Sagayama,Katsunobu Itou,Akinori Ito,Mikio Yamamoto,Atsushi Yamada,Takehito Utsuro,Kiyohiro Shikano +11 more
TL;DR: ICSLP2000: the 6th International Conference on Spoken Language Processing, October 16-20, 2000, Beijing, China.
Proceedings ArticleDOI
A new phonetic tied-mixture model for efficient decoding
TL;DR: A phonetic tied-mixture model for efficient large vocabulary continuous speech recognition that enables the decoder to perform efficient Gaussian pruning and it is found out that computing only two out of 64 components does not cause any loss of accuracy.
Proceedings ArticleDOI
Gaussian mixture selection using context-independent HMM
TL;DR: The proposed method achieves comparable performance as the standard Gaussian selection, and performs much better under aggressive pruning condition, and acoustic matching cost is reduced to almost 14% with little loss of accuracy.