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. 4. The computer-implemented method of claim 1 , wherein selecting the best transcription hypothesis based on a combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses includes: evaluating a weighting of the speech recognition scores and the co-occurrence scores; and in response to identifying that a given hypothesis has a co-occurrence score based on proposed query terms identified as co-occurring within a predetermined number of consecutive words within individual Web documents, increasing a weighting of the co-occurrence score relative to a baseline weighting.