19. A method for performing speech-to-text conversion, the method comprising: at an electronic device having a processor and memory: receiving speech input; traversing, based on the speech input, a sequence of states and arcs of a weighted finite state transducer (WFST), wherein: the sequence of states and arcs represents one or more history candidate words and a current candidate word; and a first probability of the candidate word given the one or more history candidate words is determined by traversing the sequence of states and arcs of the WFST; traversing a negating finite state transducer (FST), wherein traversing the negating FST negates the first probability of the candidate word given the one or more history candidate words; composing a virtual FST using a neural network language model and based on the sequence of states and arcs of the WFST, wherein one or more virtual states of the virtual FST represent the current candidate word; traversing the one or more virtual states of the virtual FST, wherein a second probability of the candidate word given the one or more history candidate words is determined by traversing the one or more virtual states of the virtual FST; determining, based on the second probability of the candidate word given the one or more history candidate words, text corresponding to the speech input; based on the determined text, performing one or more tasks to obtain a result; and causing the result to be presented in spoken or visual form.
19. A method for performing speech-to-text conversion, the method comprising: at an electronic device having a processor and memory: receiving speech input; traversing, based on the speech input, a sequence of states and arcs of a weighted finite state transducer (WFST), wherein: the sequence of states and arcs represents one or more history candidate words and a current candidate word; and a first probability of the candidate word given the one or more history candidate words is determined by traversing the sequence of states and arcs of the WFST; traversing a negating finite state transducer (FST), wherein traversing the negating FST negates the first probability of the candidate word given the one or more history candidate words; composing a virtual FST using a neural network language model and based on the sequence of states and arcs of the WFST, wherein one or more virtual states of the virtual FST represent the current candidate word; traversing the one or more virtual states of the virtual FST, wherein a second probability of the candidate word given the one or more history candidate words is determined by traversing the one or more virtual states of the virtual FST; determining, based on the second probability of the candidate word given the one or more history candidate words, text corresponding to the speech input; based on the determined text, performing one or more tasks to obtain a result; and causing the result to be presented in spoken or visual form. 21. The method of claim 19 , wherein the virtual FST is composed after traversing the sequence of states and arcs of the WFST.