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 . 4. The parameters adjustment method in a statistical machine translation, according to claim 1 , characterized in that, the objective function has a solving process which comprises the steps of: Step a: the processor of the computing machine finding the partial derivative for each parameters in the objective functions and obtaining ∂ ∂ λ k = ∑ s = 1 n ⁢ ⁢ [ - h k ⁡ ( f s , e s ) + ∑ e ′ ∈ C s ⁢ exp ⁢ { Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( f s , e ′ ) + l ⁡ ( e ′ , e s ) } Σ e ′ ∈ C s ⁢ exp ⁢ { Σ m = 1 M ⁢ λ m ⁢ h m ⁡ ( f s , e ′ ) + l ⁢ ( e ′ , e s ) } ⁢ h k ⁡ ( f s , e ′ ) ] ; Step b: the processor of the computing machine initializing λ m , m=1, . . . , M, a random value between [−1, 1], then according to the formula in the step a, for the partial derivative for each parameter, calculating the reciprocal value δ m , m=1, . . . , M, M refers to the total number of characteristics; Step c: the processor of the computing machine updating the value of λ m , {circumflex over (λ)} m=λ m − αδ m , m=1, . . . , M; Step d: the processor of the computing machine repeating step b and step c until |{circumflex over (λ)} m −λ m |<10−5, m=1, . . . , M.