Multilingual speech recognition at Dragon Systems

Barnett, James A.; Corrada, A.; Gao, Guoming; Gillick, Larry; Ito, Yoshiko; Lowe, Steve; Manganaro, Linda; Peskin, Barbara

doi:10.1109/icslp.1996.607239

Cited by 12 publications

(3 citation statements)

References 2 publications

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“…Recognition systems developed originally for one language have been successfully ported to several languages, including systems developed by IBM (Cohen et al, 1997), Dragon (Barnett et al, 1996), BBN (Billa et al, 1997), Cambridge (Young et al, 1997), Philips (Dugast et al, 1995), MIT (Glass et al, 1995), and LIMSI (Lamel et al, 1995). The transformation of English systems to such diverse languages like German, Japanese, French, and Mandarin Chinese illustrates that speech technology generalizes across languages and that similar modeling assumptions hold for various languages.…”

Section: Introductionmentioning

confidence: 99%

Language-independent and language-adaptive acoustic modeling for speech recognition

Schultz

Waibel

2001

Speech Communication

329

222

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With the distribution of speech technology products all over the world, the portability to new target languages becomes a practical concern. As a consequence our research focuses on the question of how to port LVCSR systems in a fast and efficient way. More specifically we want to estimate acoustic models for a new target language using speech data from varied source languages, but only limited data from the target language. For this purpose we introduce different methods for multilingual acoustic model combination and a polyphone decision tree specialization procedure. Recognition results using language dependent, independent and language adaptive acoustic models are presented and discussed in the framework of our GlobalPhone project which investigates LVCSR systems in 15 languages.

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Section: Introductionmentioning

confidence: 99%

Language-independent and language-adaptive acoustic modeling for speech recognition

Schultz

Waibel

2001

Speech Communication

329

222

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“…In the nineties, ASR systems developed originally for one language had been successfully ported to other languages, including systems developed by IBM (Cohen et al, 1997), Dragon (Barnett et al, 1996), BBN (Billa et al, 1997), Cambridge (Young et al, 1997), Philips (Dugast et al, 1995), MIT (Glass et al, 1995), and LIMSI (Lamel et al, 1995). The transformation of English systems to such diverse languages like German, Japanese, French, and Mandarin Chinese illustrated that speech technology generalizes across languages and that similar modeling assumptions hold for various languages.…”

Section: Short History On Under-resourced Language Researchmentioning

confidence: 99%

Automatic speech recognition for under-resourced languages: A survey

Besacier

Barnard

Karpov

et al. 2014

Speech Communication

407

195

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Speech processing for under-resourced languages is an active field of research, which has experienced significant progress during the past decade. We propose, in this paper, a survey that focuses on automatic speech recognition (ASR) for these languages. The definition of under-resourced languages and the challenges associated to them are first defined. The main part of the paper is a literature review of the recent (last 8 years) contributions made in ASR for under-resourced languages. Examples of past projects and future trends when dealing with under-resourced languages are also presented. We believe that this paper will be a good starting point for anyone interested to initiate research in (or operational development of) ASR for one or several under-resourced languages. It should be clear, however, that many of the issues and approaches presented here, apply to speech technology in general (text-to-speech synthesis for instance).

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“…But, for the special case of small-or medium-size vocabulary, the performance will be good enough for real applications. Actually, some useful and practical applications have been developed in the past few years [2,3].…”

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confidence: 99%