819 research outputs found
Dual Language Models for Code Switched Speech Recognition
In this work, we present a simple and elegant approach to language modeling
for bilingual code-switched text. Since code-switching is a blend of two or
more different languages, a standard bilingual language model can be improved
upon by using structures of the monolingual language models. We propose a novel
technique called dual language models, which involves building two
complementary monolingual language models and combining them using a
probabilistic model for switching between the two. We evaluate the efficacy of
our approach using a conversational Mandarin-English speech corpus. We prove
the robustness of our model by showing significant improvements in perplexity
measures over the standard bilingual language model without the use of any
external information. Similar consistent improvements are also reflected in
automatic speech recognition error rates.Comment: Accepted at Interspeech 201
Pronunciation Modeling of Foreign Words for Mandarin ASR by Considering the Effect of Language Transfer
One of the challenges in automatic speech recognition is foreign words
recognition. It is observed that a speaker's pronunciation of a foreign word is
influenced by his native language knowledge, and such phenomenon is known as
the effect of language transfer. This paper focuses on examining the phonetic
effect of language transfer in automatic speech recognition. A set of lexical
rules is proposed to convert an English word into Mandarin phonetic
representation. In this way, a Mandarin lexicon can be augmented by including
English words. Hence, the Mandarin ASR system becomes capable to recognize
English words without retraining or re-estimation of the acoustic model
parameters. Using the lexicon that derived from the proposed rules, the ASR
performance of Mandarin English mixed speech is improved without harming the
accuracy of Mandarin only speech. The proposed lexical rules are generalized
and they can be directly applied to unseen English words.Comment: Published by INTERSPEECH 201
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