1. A computer-implemented method for executing a voice search, the computer-implemented method comprising: receiving a spoken query; identifying, via an automated speech recognition process, multiple transcription hypotheses based on the spoken query, each respective transcription hypothesis being a proposed textual representation of the spoken query, each respective transcription hypothesis including a speech recognition score that indicates a probability of being a correct conversion of the spoken query to a text query; evaluating a portion of the transcription hypotheses using a co-occurrence identification process, the co-occurrence identification process identifying a frequency that proposed query terms, from each respective transcription hypothesis, co-occur within individual Web documents from a corpus of web documents, the co-occurrence identification process assigning a co-occurrence score to each respective transcription hypothesis from the portion of the transcription hypotheses, the co-occurrence score representing a measure of semantic relation of the proposed query terms based on identified co-occurrence frequencies including identifying non-sequential co-occurrences of the proposed query terms within the individual Web documents; selecting a best transcription hypothesis based on a combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses; and receiving search results, from an information retrieval system, based on a text query corresponding to the best transcription hypothesis.
1. A computer-implemented method for executing a voice search, the computer-implemented method comprising: receiving a spoken query; identifying, via an automated speech recognition process, multiple transcription hypotheses based on the spoken query, each respective transcription hypothesis being a proposed textual representation of the spoken query, each respective transcription hypothesis including a speech recognition score that indicates a probability of being a correct conversion of the spoken query to a text query; evaluating a portion of the transcription hypotheses using a co-occurrence identification process, the co-occurrence identification process identifying a frequency that proposed query terms, from each respective transcription hypothesis, co-occur within individual Web documents from a corpus of web documents, the co-occurrence identification process assigning a co-occurrence score to each respective transcription hypothesis from the portion of the transcription hypotheses, the co-occurrence score representing a measure of semantic relation of the proposed query terms based on identified co-occurrence frequencies including identifying non-sequential co-occurrences of the proposed query terms within the individual Web documents; selecting a best transcription hypothesis based on a combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses; and receiving search results, from an information retrieval system, based on a text query corresponding to the best transcription hypothesis. 12. The computer-implemented method of claim 1 , further comprising: evaluating the portion of the transcription hypotheses using a word relatedness identification process, the word relatedness identification process including evaluating a given query term, from a respective transcription hypothesis, using a lexical database, the word relatedness identification process assigning a word relatedness score to the given query term, the word relatedness score indicating a measure of semantic relation of the given query term to other words; and wherein selecting the best transcription hypothesis based on the combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses includes basing selection on word relatedness scores.