TR2017-182
Language Independent End-to-End Architecture For Joint Language and Speech Recognition
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- "Language Independent End-to-End Architecture For Joint Language and Speech Recognition", IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), DOI: 10.1109/ASRU.2017.8268945, December 2017.BibTeX TR2017-182 PDF Video
- @inproceedings{Watanabe2017dec,
- author = {Watanabe, Shinji and Hori, Takaaki and Hershey, John R.},
- title = {Language Independent End-to-End Architecture For Joint Language and Speech Recognition},
- booktitle = {IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)},
- year = 2017,
- month = dec,
- doi = {10.1109/ASRU.2017.8268945},
- url = {https://www.merl.com/publications/TR2017-182}
- }
,
- "Language Independent End-to-End Architecture For Joint Language and Speech Recognition", IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), DOI: 10.1109/ASRU.2017.8268945, December 2017.
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Research Areas:
Abstract:
End-to-end automatic speech recognition (ASR) can significantly reduce the burden of developing ASR systems for new languages, by eliminating the need for linguistic information such as pronunciation dictionaries. This also creates an opportunity, which we fully exploit in this paper, to build a monolithic multilingual ASR system with a language-independent neural network architecture. We present a model that can recognize speech in 10 different languages, by directly performing grapheme (character/chunked-character) based speech recognition. The model is based on our hybrid attention/connectionist temporal classification (CTC) architecture which has previously been shown to achieve the state-of-the-art performance in several ASR benchmarks. Here we augment its set of output symbols to include the union of character sets appearing in all the target languages. These include Roman and Cyrillic Alphabets, Arabic numbers, simplified Chinese, and Japanese Kanji/Hiragana/Katakana characters (5,500 characters in all). This allows training of a single multilingual model, whose parameters are shared across all the languages. The model can jointly identify the language and recognize the speech, automatically formatting the recognized text in the appropriate character set. The experiments, which used speech databases composed of Wall Street Journal (English), Corpus of Spontaneous Japanese, HKUST Mandarin CTS, and Voxforge (German, Spanish, French, Italian, Dutch, Portuguese, Russian), demonstrate comparable/superior performance relative to language-dependent end-to-end ASR systems.
Related News & Events
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Where: Tokyo, Japan
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Research Area: Speech & AudioBrief- Mitsubishi Electric Corporation announced that it has developed the world's first technology capable of highly accurate multilingual speech recognition without being informed which language is being spoken. The novel technology, Seamless Speech Recognition, incorporates Mitsubishi Electric's proprietary Maisart compact AI technology and is built on a single system that can simultaneously identify and understand spoken languages. In tests involving 5 languages, the system achieved recognition with over 90 percent accuracy, without being informed which language was being spoken. When incorporating 5 more languages with lower resources, accuracy remained above 80 percent. The technology can also understand multiple people speaking either the same or different languages simultaneously. A live demonstration involving a multilingual airport guidance system took place on February 13 in Tokyo, Japan. It was widely covered by the Japanese media, with reports by all six main Japanese TV stations and multiple articles in print and online newspapers, including in Japan's top newspaper, Asahi Shimbun. The technology is based on recent research by MERL's Speech and Audio team.
Link:
Mitsubishi Electric Corporation Press Release
Media Coverage:
NHK, News (Japanese)
NHK World, News (English), video report (starting at 4'38")
TV Asahi, ANN news (Japanese)
Nippon TV, News24 (Japanese)
Fuji TV, Prime News Alpha (Japanese)
TV Tokyo, World Business Satellite (Japanese)
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The Nikkei Shimbun (Japanese)
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Response (Japanese).
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