A Romanian language modeling using linguistic factors

Lazar, Marilena; Militaru, Diana

doi:10.1109/sped.2013.6682649

Cited by 2 publications

(2 citation statements)

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“…One of these methods-min/max counts-was used by the authors in [8]. The authors in [7] also proposed to using several backoff paths simultaneously and determining the set of those paths in run-time.…”

Section: Previous Workmentioning

confidence: 99%

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Context-dependent factored language models

Donaj

KaăźIăź

2017

J AUDIO SPEECH MUSIC PROC.

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The incorporation of grammatical information into speech recognition systems is often used to increase performance in morphologically rich languages. However, this introduces demands for sufficiently large training corpora and proper methods of using the additional information. In this paper, we present a method for building factored language models that use data obtained by morphosyntactic tagging. The models use only relevant factors that help to increase performance and ignore data from other factors, thus also reducing the need for large morphosyntactically tagged training corpora. Which data is relevant is determined at run-time, based on the current text segment being estimated, i.e., the context. We show that using a context-dependent model in a two-pass recognition algorithm, the overall speech recognition accuracy in a Broadcast News application improved by 1.73% relatively, while simpler models using the same data achieved only 0.07% improvement. We also present a more detailed error analysis based on lexical features, comparing first-pass and second-pass results.

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Section: Previous Workmentioning

confidence: 99%

“…FLMs are often used in Arabic and Slavic languages, probably most prominently in Russian [9,10], as well as in other morphologically rich languages such as Romanian [8], Turkish [11], and Amharic [12].…”

Section: Previous Workmentioning

confidence: 99%