Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new search strategy for large vocabulary continuous Mandarin speech recognition considering the special structure of the Chinese language. This strategy is composed of forward and backward passes, beten which a high-quality syllable lattice is generated to bridge the syllable-level and word-level decoding processes. In the forward pass, considering the small number of syllables in the Chinese language, a frame-synchronous stack decoder is used to integrate the high-order syllable N-Gram language model, so as to generate a very accurate and compact syllable lattice. In the backward pass, considering the special monosyllabic wording structure in the Chinese language, the search space for the word-level decoding is expanded dynamically from the syllable lattice, and the best word sequence is extracted based on the knowledge provided by the word pronunciation lexicon and the word N-Gram language model. In the preliminary experiments, it was found that, with this strategy, the character error rate can be reduced by more than 20% as compared with a previous system using syllable-aligned lattice approach on a speaker-adaptive continuous speech recognition task.
['Tai-Hsuan Ho', 'Kae-Cherng Yang', 'Kuo-Hsun Huang', 'Lin-Shan Lee']
I am writing a research paper on a idea Improved search strategy for large vocabulary continuous Mandarin speech recognition
[{"from": "human", "value": "I am writing a research paper on a idea Improved search strategy for large vocabulary continuous Mandarin speech recognition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new search strategy for large vocabulary continuous Mandarin speech recognition considering the special structure of the Chinese language. This strategy is composed of forward and backward passes, beten which a high-quality syllable lattice is generated to bridge the syllable-level and word-level decoding processes. In the forward pass, considering the small number of syllables in the Chinese language, a frame-synchronous stack decoder is used to integrate the high-order syllable N-Gram language model, so as to generate a very accurate and compact syllable lattice. In the backward pass, considering the special monosyllabic wording structure in the Chinese language, the search space for the word-level decoding is expanded dynamically from the syllable lattice, and the best word sequence is extracted based on the knowledge provided by the word pronunciation lexicon and the word N-Gram language model. In the preliminary experiments, it was found that, with this strategy, the character error rate can be reduced by more than 20% as compared with a previous system using syllable-aligned lattice approach on a speaker-adaptive continuous speech recognition task."}]