1. A parameters adjustment method in a statistical machine translation for a computing machine, characterized in that, the method comprises the following steps: Step 1: building a language model required for translation by utilizing a monolingual corpora with a processor of a computing machine; Step 2: building a phrase translation model by utilizing a bilingual parallel corpus with the processor of the computing machine; Step 3: the processor of the computing machine processing parameters adjustment for λ m by utilizing an objective function min λ ⁢ ∑ s = 1 n ⁢ ⁢ [ - Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( e s , f s ) + log ⁢ ∑ e ∈ C s ⁢ exp ⁢ { Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( f s , e ′ ) + l ⁡ ( e ′ , e s ) } ] , where e s refers to reference translation, e′ refers to machine translation, fs refers to sentence in source language awaiting for translation processing, h m (e s , f s ) and h m (f s ,e′) refer to the characteristics used in building the translation system, the characteristics comprises four main categories, which are language model, phrase translation listing, sequence model and correctional word penalty items, m =1, . . . , M, M refers to the total number of characteristics, l(e′, e s ) refers to cost function, C 5 refers to the collection set of machine translation candidate, e′ ε C 5 .
1. A parameters adjustment method in a statistical machine translation for a computing machine, characterized in that, the method comprises the following steps: Step 1: building a language model required for translation by utilizing a monolingual corpora with a processor of a computing machine; Step 2: building a phrase translation model by utilizing a bilingual parallel corpus with the processor of the computing machine; Step 3: the processor of the computing machine processing parameters adjustment for λ m by utilizing an objective function min λ ⁢ ∑ s = 1 n ⁢ ⁢ [ - Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( e s , f s ) + log ⁢ ∑ e ∈ C s ⁢ exp ⁢ { Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( f s , e ′ ) + l ⁡ ( e ′ , e s ) } ] , where e s refers to reference translation, e′ refers to machine translation, fs refers to sentence in source language awaiting for translation processing, h m (e s , f s ) and h m (f s ,e′) refer to the characteristics used in building the translation system, the characteristics comprises four main categories, which are language model, phrase translation listing, sequence model and correctional word penalty items, m =1, . . . , M, M refers to the total number of characteristics, l(e′, e s ) refers to cost function, C 5 refers to the collection set of machine translation candidate, e′ ε C 5 . 2. The parameters adjustment method in a statistical machine translation, according to claim 1 , characterized in that, in the objective function of the step 3, l ⁡ ( e ′ , e s ) = - BP ⁡ ( e ′ , e s ) * exp ⁡ ( ∑ n = 1 N ⁢ ⁢ log ⁢ ⁢ p n N ) , where BP(e′, e s ) refers to penalty factor for length, that penalty is given to a sentence having a shorter length than the reference translation, p n , refers to N-gram accuracy in N-gram for representing the proportion of matching between the n-gram phrases in machine translation and n-gram reference translation, N refers to the maximum order used in N-gram.