1. A method comprising: classifying, at a computing system, a set of benchmark text strings to provide a set of benchmark classifications, wherein the benchmark text strings correspond to a benchmark corpus of benchmark utterances; determining a respective classification for multiple text strings in a corpus of text strings; sampling text strings from the corpus of text strings to form a training corpus of training text strings, such that particular classifications of the sampled text strings occur in proportion to occurrences of the particular classifications for the benchmark text strings; and training an automatic speech recognition (ASR) system with the training corpus of training text strings.
1. A method comprising: classifying, at a computing system, a set of benchmark text strings to provide a set of benchmark classifications, wherein the benchmark text strings correspond to a benchmark corpus of benchmark utterances; determining a respective classification for multiple text strings in a corpus of text strings; sampling text strings from the corpus of text strings to form a training corpus of training text strings, such that particular classifications of the sampled text strings occur in proportion to occurrences of the particular classifications for the benchmark text strings; and training an automatic speech recognition (ASR) system with the training corpus of training text strings. 2. The method of claim 1 , wherein the set of benchmark classifications comprise topic classifications.