A method for speech synthesis comprising: obtaining to-be-processed linguistic data; encoding, by a first encoder, the linguistic data, to obtain encoded linguistic data; obtaining an embedded vector for speech feature conversion, the embedded vector being generated according to a residual between synthesized reference speech data and reference speech data that correspond to the same reference linguistic data, wherein the embedded vector is a vector having a speaking style feature of a reference object; and decoding, by a first decoder, the encoded linguistic data according to the embedded vector, to obtain target synthesized speech data on which the speech feature conversion is performed, wherein the target synthesized speech data has the speaking style of the reference object. wherein the embedded vector for speech feature conversion is determined by: obtaining reference linguistic data and corresponding reference speech data, wherein the corresponding reference speech data has a style feature; encoding, by a second encoder, the reference linguistic data, to obtain encoded reference linguistic data, wherein the reference linguistic data is processed by using the second encoder to obtain a context representation representing the reference linguistic data, and the context representation is a vector summarizing an input sequence X = { x, x... x ( n)}, where n is an integer greater than 1; decoding, by a second decoder, the encoded reference linguistic data, to obtain synthesized reference speech data, wherein the synthesized reference speech data has no style feature, and the synthesized reference speech data is obtained by inputting the context representation into the second decoder, and generating an output sequence Y = { y, y... y ( n)} by using a vector of a fixed length as a condition, to obtain synthesized reference speech data; and determining an embedded vector for speech feature conversion according to a residual between the reference speech data and the synthesized reference speech data, wherein the embedded vector is obtained by using a residual model. obtaining to-be-processed linguistic data; encoding, by a first encoder, the linguistic data, to obtain encoded linguistic data; obtaining an embedded vector for speech feature conversion, the embedded vector being generated according to a residual between synthesized reference speech data and reference speech data that correspond to the same reference linguistic data, wherein the embedded vector is a vector having a speaking style feature of a reference object; and decoding, by a first decoder, the encoded linguistic data according to the embedded vector, to obtain target synthesized speech data on which the speech feature conversion is performed, wherein the target synthesized speech data has the speaking style of the reference object. wherein the embedded vector for speech feature conversion is determined by: obtaining reference linguistic data and corresponding reference speech data, wherein the corresponding reference speech data has a style feature; encoding, by a second encoder, the reference linguistic data, to obtain encoded reference linguistic data, wherein the reference linguistic data is processed by using the second encoder to obtain a context representation representing the reference linguistic data, and the context representation is a vector summarizing an input sequence X = { x, x... x ( n)}, where n is an integer greater than 1; decoding, by a second decoder, the encoded reference linguistic data, to obtain synthesized reference speech data, wherein the synthesized reference speech data has no style feature, and the synthesized reference speech data is obtained by inputting the context representation into the second decoder, and generating an output sequence Y = { y, y... y ( n)} by using a vector of a fixed length as a condition, to obtain synthesized reference speech data; and determining an embedded vector for speech feature conversion according to a residual between the reference speech data and the synthesized reference speech data, wherein the embedded vector is obtained by using a residual model. obtaining reference linguistic data and corresponding reference speech data, wherein the corresponding reference speech data has a style feature; encoding, by a second encoder, the reference linguistic data, to obtain encoded reference linguistic data, wherein the reference linguistic data is processed by using the second encoder to obtain a context representation representing the reference linguistic data, and the context representation is a vector summarizing an input sequence X = { x, x... x ( n)}, where n is an integer greater than 1; decoding, by a second decoder, the encoded reference linguistic data, to obtain synthesized reference speech data, wherein the synthesized reference speech data has no style feature, and the synthesized reference speech data is obtained by inputting the context representation into the second decoder, and generating an output sequence Y = { y, y... y ( n)} by using a vector of a fixed length as a condition, to obtain synthesized reference speech data; and determining an embedded vector for speech feature conversion according to a residual between the reference speech data and the synthesized reference speech data, wherein the embedded vector is obtained by using a residual model.