Comparative Experiments on Large Vocabulary Speech Recognition
BBN SYSTEMS AND TECHNOLOGIES CORP CAMBRIDGE MA
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This paper describes several key experiments in large vocabulary speech recognition. We demonstrate that, counter to our intuitions, given a fixed amount of training speech, the number of training speakers has little effect on the accuracy. We show how much speech is needed for speaker-independent SI recognition in order to achieve the same performance as speaker-dependent SD recognition. We demonstrate that, though the N-Best Paradigm works quite well up to vocabularies of 5,000 words, it begins to break down with 20,000 words and long sentences. We compare the performance of two feature preprocessing algorithms for microphone independence and we describe a new microphone adaptation algorithm based on selection among several codebook transformations.
- Electrical and Electronic Equipment
- Voice Communications